Note: Some publications are made on-line available for
faster dissemination. The copyright of the papers is owned by their publisher.
Source code is for free use for academic research ONLY.
Publications of Yaochu Jin
My citation profiles as of 03.12.2022:
Orcid: https://orcid.org/0000-0003-1100-0631
Google
Scholar: h-index: 92, i10-index: 331, citations: 35,842
Web
of Science, h-index: 70, citations:
19,438.
Scopus
Author Profile: h-index=74, citations = 22,148.
Research
Gate: h-index: 85, citations: 29,895.
DBLP Computer Science Bibliography.
PlatEMO, a Single-, Multi- and Many-objective
Optimization Tool
1. Haoran
Gu, Handing Wang, and Yaochu Jin. Surrogate-assisted differential
evolution with adaptive multi-subspace search for large-scale expensive
optimization. IEEE Transactions on Evolutionary Computation, 2022
(accepted)
2.
Shiqiang Zhu, Ting Yu, Tao Xu, Hongyang
Chen, Schahram Dustdar, Sylvain Gigan, Deniz Gunduz, Ekram Hossain, Yaochu
Jin, Feng Lin, Bo Liu, Zhiguo Wan, Ji Zhang, Zhifeng Zhao, Wentao Zhu,
Zuoning Chen, Tariq Durrani, Huaimin Wang, Jiangxing Wu, Tongyi Zhang, Yunhe
Pan. Intelligent computing: The latest advances, challenges, and future. Intelligent
Computing, 2022 (accepted)
3.
Jinghao Zhang, Zhenhua Feng, Guosheng Hu and
Yaochu Jin. MixProp: Towards high-performance image recognition via dual
batch normalisation. International Workshop on Multimodal Video Search by
Examples. A BMVC 2022 Workshop, 24th November 2022
4.
Yan Zhou, Yaochu
Jin, Yao Sun, and Jinliang Ding. Surrogate-assisted cooperative
co-evolutionary reservoir architecture search for liquid state machines. IEEE
Transactions on Emerging Topics in Computational Intelligence, 2022
(accepted)
5.
Zhen Yang, Jie Zhang, Yunliang Jiang, and Yaochu Jin. A
self-organizing IoT service perception algorithm based on human visual
direction sensitive system. IEEE
Internet of Things Journal, 2022 (accepted)
6.
Shangshang Yang, Haoyu Wei, Haiping Ma, Ye
Tian, Xingyi Zhang, Yunbo Cao, and Yaochu Jin. Cognitive diagnosis-based
personalized exercise group assembly via a multi-objective evolutionary
algorithm. IEEE Transactions on Emerging Topics in Computational
Intelligence, 2022 (accepted)
7.
Minyang Chen, Wei Du,
Yang Tang, Yaochu Jin, and Gary G. Yan. A
decomposition method for both additively and non-additively separable problems. IEEE Transactions on Evolutionary
Computation, 2022 (accepted)
8.
Ye Tian, Weijian Zhu, Xingyi Zhang, and Yaochu
Jin. A practical tutorial on solving optimization
problems via PlatEMO. Neurocomputing, 2022 (accepted)
9.
Shiqing Liu, Haoyu Zhang, and Yaochu Jin.
A survey on computationally efficient neural
architecture search. Journal of Automation and Intelligence,
2022
10.
Lianghao Li, Cheng He, Ran Cheng, Hongbin
Li, Linqiang Pan, and Yaochu Jin. A fast sampling based evolutionary algorithm
for million-dimensional multiobjective optimization. Swarm and Evolutionary Computation,
75, 101181, 2022
11.
Cheng He, Ran Cheng, Lianghao Li, Tan Kay
Chen, and Yaochu Jin. Evolutionary
large-scale multiobjective optimization using reformulation based decision
variable analysis. IEEE Transactions on Evolutionary
Computation, 2022
12. Xiaoshu Xiang, Ye Tian, Ran Cheng, Xingyi Zhang, Shengxiang Yang and Yaochu Jin. A benchmark generator for online dynamic single-objective and multi-objective optimization problems. Information Sciences, 2022
13. Rui Wang, Oguzhan Ersoy, Hangyu Zhu, Yaochu Jin, and Kaitai Liang. FEVERLESS: Fast and secure vertical federated learning based on XGBoost for decentralized labels. IEEE Transactions on Big Data, 2022 (minor revision)
14. Shaotao Chen, Xihe Qiu, Xiaoyu Tan, Zhijun Fang, and Yaochu Jin. A model-based hybrid soft actor-critic deep reinforcement learning algorithm for optimal ventilator settings. Information Sciences, 2022 (accepted)
15. Meirong Chen, Yinan Guo, Yaochu Jin, Shengxiang Yang, Dunwei Gong, and Zekuan Yu. An environment-driven hybrid evolutionary algorithm for dynamic multi-objective optimization problems. Complex & Intelligent Systems, 2022 (accepted)
16. Ye Tian, Xinyi Zhang, Cheng He Cheng, Kay Chen Tan, and Yaochu Jin. Principled design of translation, scale, and rotation invariant variation operators for metaheuristics. Chinese Journal of Electronics, 2022 (accepted)
17. Qiqi Liu, Yaochu Jin, Martin Heiderich, and Tobias Rodemann. Coordinated Adaptation of Reference Vectors and Scalarizing Functions in Evolutionary Many-objective Optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022 (accepted)
18. Ye Tian, Langchun Si, Xingyi Zhang, Kay Chen Tan, and Yaochu Jin. Local model based Pareto front estimation for multi-objective optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022 (accepted)
19. Xinjie Wang, Yaochu Jin, Wenli Du, and Jun Wang. Evolving dual-threshold Bienenstock-Cooper-Munro learning rules in Echo State Networks. IEEE Transactions on Neural Networks and Learning Systems, 2022 (accepted)
20. Tuo Zhang, Handing Wang, Bo Yuan, Yaochu Jin, and Xin Yao. Surrogate-assisted evolutionary Q-learning for black-box dynamic time-linkage optimization problems. IEEE Transactions on Evolutionary Computation, 2022 (accepted)
21.
Yapei Wu, Xingguang Peng, Handing Wang, Yaochu
Jin, and Demin Xu. Cooperative coevolutionary CMA-ES with landscape-aware grouping in
noisy environments. IEEE Transactions on Evolutionary
Computation, 2022 (accepted)
22.
Zhihua Liu, Lei Tong, Long Chen, Zheheng
Jiang, Feixiang Zhou, Qianni Zhang, Xiangrong Zhang, Yaochu Jin, and
Huiyu Zhou. Deep Learning Based Brain Tumor
Segmentation: A Survey. Complex & Intelligent Systems,
2022 (accepted)
23.
Foivos Ntelemis, Yaochu Jin, and
Spencer A. Thomas. Information maximization clustering via
multi-view self-labelling. Knowledge-Based Systems, 2022
(accepted)
Code uploaded in GitHub
24.
Ye Tian, Haowen Chen, Haiping Ma, Xingyi
Zhang, Kay Chen Tan and Yaochu Jin. Integrating conjugate gradients into
evolutionary algorithms for large-scale continuous multi-objective optimization. IEEE/CAA Journal of Automatica Sinica,
2022 (accepted)
25.
Zhening Liu, Handing Wang and Yaochu Jin.
Performance indicator based adaptive model
selection for offline data-driven multi-objective evolutionary optimization. IEEE Transactions on Cybernetics,
2022 (accepted)
26.
Xiangyu Wang, Bingran
Zhang, Jian Wang, Kai Zhang, and Yaochu Jin. A cluster-based competitive particle swarm
optimizer with a sparse truncation operator for multi-objective optimization. Swarm and Evolutionary Computation,
2022 (accepted)
27.
Ye Tian, Jingwen Pan, Shangshang Yang,
Xingyi Zhang, Shuping He, and Yaochu Jin. Imperceptible and sparse adversarial attacks
via a dual-population based constrained evolutionary algorithm. IEEE Transactions on Artificial
Intelligence, 2022 (accepted)
28. Hui
Bai, Ran Cheng, Danial Yazdani, Kay Chen Tan, and Yaochu Jin. Evolutionary large-scale
dynamic optimization using bi-level variable grouping. IEEE
Transactions on Cybernetics, 2022 (accepted)
29. Patrick Brosnan, Guohong Tian,
Hongguang Zhang, Zhong Wu, and Yaochu Jin. Non-linear and multi-domain modelling
of a permanent magnet linear synchronous machine for free piston engine
generators. Energy Conversion and Management: X, 100195, 2022
(accepted)
30. Ye Tian, Xiaopeng Li, Haiping Ma,
Xingyi Zhang, Kay Chen Tan, and Yaochu Jin. Deep reinforcement learning
based adaptive operator selection for evolutionary multi-objective optimization. IEEE Transactions on Emerging
Topics in Computational Intelligence, 2022 (accepted)
31. Qiqi Liu, Yaochu Jin, Martin
Martin Heiderich, and Tobias Rodemann. Surrogate-assisted
evolutionary optimization of expensive many-objective irregular problems. Knowledge-Based Systems, 2022
(accepted)
32.
Hangyu Zhu, Rui Wang, Yaochu Jin, and Kaitai
Liang. PIVODL: Privacy-preserving
vertical federated learning over distributed labels. IEEE Transactions
on Artificial Intelligence, 2021 (accepted)
33.
Guo Yu,
Yaochu Jin, Markus Olhofer, Qiqi Liu, and Wenli Du. Solution set augmentation
for knee identification in multiobjective decision analysis. IEEE
Transactions on Cybernetics, 2021 (accepted)
34. Yan Xiao, Yaochu Jin, and Kuangrong Hao. Adaptive prototypical
networks with label words and joint representation learning for few-shot
relation classification. IEEE
Transactions on Neural Networks and Learning Systems, 2021 (accepted)
35.
Ye Tian, Shichen Peng, Shangshang Yang, Xingyi Zhang,
Kay Chen Tan and Yaochu Jin. Action command encoding for
surrogate assisted neural architecture search. IEEE Transactions on Cognitive and Developmental Systems, 2021
(accepted)
36.
Foivos Ntelemis, Yaochu
Jin, and Spencer A. Thomas. Image clustering using an
augmented generative adversarial network and information maximization. IEEE Transactions on Neural Networks and
Learning Systems, 2021 (accepted)
37.
Tonghao Wang, Xingguang Peng, Yaochu Jin and Demin Xu. Experience
sharing based memetic transfer learning for multiagent reinforcement learning.
Memetic Computing, 2021 (accepted)
38.
Qiqi Liu, Yaochu Jin, Martin Heiderich, Tobias Rodemann and Guo Yu. An adaptive reference
vector guided evolutionary algorithm using growing neural gas for
many-objective optimization of irregular problems. IEEE Transactions on Cybernetics, 2020 (accepted)
39. Ye Tian, Yuandong Feng, Chao Wang, Ruifen
Cao, Xingyi Zhang, Xi Pei, Kay Chen Tan, and Yaochu Jin. A large-scale combinatorial many-objective
evolutionary algorithm for intensity-modulated radiotherapy planning. IEEE Transactions on Evolutionary
Computation, 26(6): 1511-1525, 2022
40. Guo Yu, Lianbo Ma, Yaochu Jin,
Wenli Du, Qiqi Liu, and Hengmin Zhang. A survey on knee-oriented
multi-objective evolutionary optimization. IEEE Transactions on
Evolutionary Computation, 26(6):1452-1472, 2022
41. Qiqi Liu, Ran Cheng, Yaochu Jin,
Martin Heiderich, and Tobias Rodemann. Reference vector assisted
adaptive model management for surrogate-assisted many-objective optimization. IEEE Transactions on Systems,
Man, and Cybernetics – Systems, 52(12): 7760-7773,
2022
42. Sutong Wang, Dujuan Wang, Yunqiang Yin,
Yanzhang Wang, and Yaochu Jin. Interpretability-based
multimodal convolutional neural networks for skin lesion diagnosis. IEEE
Transactions on Cybernetics,
52(12): 12623-12637,
2022
43. Sheng Qi, Juan Zou, Shengxiang Yang, Yaochu Jin, Jinhua Zheng, Xu Yang. A self-exploratory competitive swarm optimization algorithm for large-scale multiobjective optimization. Information Sciences, 609: 1601-1620, 2022
44. Yitian Hong, Yaochu Jin, and Yang Tang. Rethinking individual global max in cooperative multi-agent reinforcement learning. The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, November 26 - December 4, 2022
45. Guoyang Xie, Jinbao Wang, Yawen Huang, Yefeng Zheng, Feng Zheng, and Yaochu Jin. FedMed-ATL: Misaligned unpaired brain image synthesis via affine transform loss. The 30th ACM International Conference on Multimedia (ACM MM 2022), 2022
46. Haoyu
Zhang, Yaochu Jin, and Kuangrong Hao. Evolutionary search for complete neural network
architectures with partial weight sharing. IEEE
Transactions on Evolutionary Computation, 26(5): 1072-1086,
2022
47. Xiangyu Wang, Kai Zhang, Jian Wang,
and Yaochu Jin. An Enhanced competitive swarm optimizer with strongly convex
sparse operator for large-scale multi-objective optimization.
IEEE
Transactions on Evolutionary Computation, 26(5): 859-871,
2022
48. Xinjie Wang, Yaochu
Jin and Kuangrong Hao. Computational modeling of structural synaptic plasticity in
echo state networks. IEEE
Transactions on Cybernetics, 52(10): 11254-11266, 2022
49.
Shangshang Yang and Ye Tian and Cheng
He and Xingyi Zhang and Kay Chen Tan, and Yaochu
Jin. A gradient
guided evolutionary approach to training deep neural networks. IEEE Transactions on Neural Networks and
Learning Systems, 33(9): 4861-4875, 2022
50.
Ye
Tian, Yajie Zhang, Yansen Su, Xingyi Zhang, Kay Chen Tan, and Yaochu Jin. Balancing objective
optimization and constraint satisfaction in constrained evolutionary
multi-objective optimization. IEEE
Transactions on Cybernetics, 52(9): 9559-9572, 2022
51.
Ye
Tian, Chang Lu, Xingyi Zhang, Fan Cheng, and Yaochu Jin. A
pattern mining based evolutionary algorithm for large-scale sparse
multi-objective optimization problems. IEEE Transactions on Cybernetics, 52(7): 6784-6797, 2022
52.
Xilu Wang, Yaochu Jin, Sebastian Schmitt, and
Markus Olhofer. Transfer
learning based co-surrogate assisted evolutionary bi-objective optimization for
objectives with non-uniform evaluation times. Evolutionary Computation,
30 (2): 221–251, 2022
53.
Xiaoshu
Xiang, Ye Tian, Xingyi Zhang, Jianhua Xiao and Yaochu Jin. A
pairwise proximity learning-based ant colony algorithm for dynamic vehicle
routing problems. IEEE Transactions
on Intelligent Transportation Systems, 23(6): 5275 – 5286, 2022
54. Jianchang Liu, Yuanchao Liu, Yaochu Jin, and Fei Li. A decision
variable assortment based evolutionary algorithm for dominance robust
multi-objective optimization. IEEE Transactions on Systems, Man
and Cybernetics: Systems, 52(5): 3360 – 3375, 2022
55. Hangyu
Zhu and Yaochu Jin. Real-time
federated evolutionary neural architecture search. IEEE Transactions on Evolutionary Computation, 26(2): 364-378, 2022
56.
Qing
Chen, Yaochu Jin and Yongduan Song. Fault-tolerant
adaptive tracking control of Euler-Lagrange systems — An echo state network
approach driven by reinforcement learning. Neurocomputing, 481:109-116,
2022
57.
Yan
Xiao, Yaochu Jin, Ran Cheng, and Kuangrong Hao. Hybrid
attention-based transformer block model for distant supervision relation
extraction. Neurocomputing, 470: 29-39, 2022
58. Jinjin Xu, Wenli Du, Yaochu Jin,
Wangli He, and Ran Cheng. Ternary
compression for communication-efficient federated learning. IEEE Transactions on Neural Networks and
Learning Systems, 33(3): 1162-1176, 2022
59.
Dan Guo, Xilu Wang, Kailai Gao, Yaochu Jin, Jinliang Ding, and Tianyou
Chai. Evolutionary
optimization of high-dimensional multi- and many-objective expensive problems
assisted by a dropout neural network. IEEE
Transactions on Systems, Man and Cybernetics: Systems, 52(4): 2084-2097,
2022
Matlab code on
GitHub
60. Yuanchao
Liu, Jianchang Liu, and Yaochu Jin. Surrogate-assisted
multi-population particle swarm optimizer for high-dimensional expensive optimization.
IEEE Transactions on Systems, Man
and Cybernetics: Systems, 52(4): 2084-2097, 2022
61.
Yajun Ru, Xihe Qiu, Xiaoyu Tan, Bin Chen, Yongbin Gao,
and Yaochu Jin. Sparse-attentive
meta temporal point process for clinical decision support, Neurocomputing,
485: 114-123, 2022
62.
Dong Han, Wenli Du, Yaochu Jin, Wei Du, and Guo
Yu. A
fuzzy constraint handling technique for decomposition-based constrained multi-
and many-objective optimization. Information Science, 597:318-340,
2022
63.
Wei Du, Wenjiang Song, Yang Tang, Yaochu Jin, and Feng Qian. Searching for robustness
intervals in evolutionary robust optimization. IEEE Transactions on Evolutionary Computation, 26(1): 58-72, 2022
64.
Ye Tian, Langchun Si, Xingyi Zhang, Ran Cheng, Cheng
He, Kay Chen Tan, and Yaochu Jin. Evolutionary large-scale
multi-objective optimization: A survey. ACM
Computing Surveys, 54(8): 174, 2022
65.
Xiaojun
Zhou, Jianpeng Long, Yaochu Jin, Guo
Yu, Chunhua Yang. A
fast constrained state transition algorithm. Neurocomputing, 470:29-39, 2022
66.
Xihe
Qiu, Xiaoyu Tan, Qiong Li, Shaotao Chen, Yajun Ru, and Yaochu Jin. A
latent batch-constrained deep reinforcement learning approach for precision
dosing clinical decision support. Knowledge-Based Systems, 237,
107689, 2022
67. Ye Tian, Chang Lu, Xingyi Zhang, and Yaochu Jin. Solving large-scale multiobjective optimization problems with sparse optimal solutions via unsupervised neural networks. IEEE Transactions on Cybernetics, 51(6): 3115 – 3128, 2021
68.
Ruochen Liu,
Jianxia Li, Yaochu Jin and Licheng
Jiao. A self-adaptive response strategy for
dynamic multi-objective evolutionary optimization based on objective space
decomposition. Evolutionary
Computation, 29 (4): 491–519, 2021
69. Jinjin Xu, Yaochu Jin, and Wenli Du. A
federated data-driven evolutionary algorithm for expensive multi/many-objective
optimization. Complex &
Intelligent Systems, 7:3093–3109, 2021
70. Ataollah Ramezan Shirazi and Yaochu Jin. Regulated morphogen gradients for target surrounding and adaptive shape formation. IEEE Transactions on Cognitive and Developmental Systems, 13(4): 818-826, 2021
71.
Xilu Wang, Yaochu
Jin, Sebastian Schmitt, Markus Olhofer, and Richard Allmendinger. Transfer
learning based surrogate assisted evolutionary bi-objective optimization for
objectives with different evaluation times. Knowledge-Based Systems, 227, 107190,
2021
72.
Zhenshou Song, Handing Wang, Cheng He,
and Yaochu Jin. A Kriging-assisted
two-archive evolutionary algorithm for expensive many-objective optimization.
IEEE Transactions on Evolutionary
Computation, 25(6):1013-1027, 2021
73.
Sutong Wang, Yunqiang Yin, Dujuan Wang, Zehui Lv,
Yanzhang Wang, and Yaochu Jin. An
interpretable deep neural network for colorectal polyp diagnosis under
colonoscopy. Knowledge-Based Systems, 234:107568, 2021
74.
Hangyu Zhu, Jinjin Xu, Shiqing Liu and Yaochu Jin. Federated
learning on non-iid data: A survey. Neurocomputing,
465: 371-390, 2021
75.
Jinjin Xu, Yaochu Jin, Wenli Du, and Sai Gu. A
federated data-driven evolutionary algorithm. Knowledge-Based Systems,
233:107532, December 2021
76. Hangyu Zhu, Rui Wang, Yaochu Jin,
Kaitai Liang, and Jianting Ning. Distributed
additive encryption and quantization for privacy preserving federated deep
learning. Neurocomputing, 463: 309-327, 2021
77. Shufen Qin, Chaoli Sun, Yaochu Jin, Ying Tan and Jonathan Fieldsend. Large-scale
evolutionary multi-objective optimization assisted by directed sampling. IEEE Transactions on Evolutionary
Computation, 25(4): 724 – 738, 2021
Matlab
code here
78.
Danial Yazdani, Ran Cheng, Donya
Yazdani, Juergen Branke, Yaochu Jin,
and Xin Yao. A survey of
evolutionary continuous dynamic optimization over two decades – Part A. IEEE Transactions on Evolutionary
Computation, 25(4): 609
– 629, 2021
79.
Danial Yazdani, Ran Cheng, Donya
Yazdani, Juergen Branke, Yaochu Jin,
and Xin Yao. A survey of
evolutionary continuous dynamic optimization over two decades – Part B. IEEE Transactions on Evolutionary
Computation, 25(4): 630 – 650,
2021
80.
Yaochu Jin, Handing Wang, Chaoli Sun. Data-driven evolutionary
optimization. Springer, June 2021
81.
Ye
Tian, Ruchen Liu, Xingyi Zhang, Haiping Ma, Kay Chen Tan, and Yaochu Jin. A multi-population
evolutionary algorithm for large-scale multi-modal multi-objective optimization
problems. IEEE Transactions on
Evolutionary Computation, 25(3): 405 – 418, 2021
82.
Shuai
Wang, Jing Liu and Yaochu Jin. A computationally
efficient evolutionary algorithm for multi-objective network robustness
optimization. IEEE Transactions on
Evolutionary Computation, 25(3): 419 – 432, 2021
83.
Cheng
He, Ran Cheng, Ye Tian, Xingyi Zhang, Kay Chen Tan, and Yaochu Jin. Paired
offspring generation for scalable constrained multiobjective optimization. IEEE Transactions on Evolutionary
Computation, 25(3): 448 – 462, 2021
84.
Jia
Liu and Yaochu Jin. Multi-objective
search of robust neural architectures against multiple types of adversarial
attacks. Neurocomputing, 453:
73-84, 2021
85. Huangke
Chen, Ran Cheng, Witold Pedrycz, and Yaochu
Jin. Solving
many-objective optimization problems via multistage evolutionary search. IEEE Transactions on Systems, Man and
Cybernetics: Systems, 51(6): 3552-3564, 2021
86.
Cheng He, Shihua Huang, Ran Cheng,
Kay Chen Tan, and Yaochu Jin. Evolutionary
multi-objective optimization driven by generative adversarial networks. IEEE Transactions on Cybernetics, 51(6):
3129-3142, 2021
87.
Huaming Chen, Fuyi Li, Lei Wang, Yaochu
Jin, Chi-Hung Chi, Lukasz Kurgan,
Jiangning Song, Jun Shen. Systematic
evaluation of machine learning methods for identifying human-pathogen
protein-protein interactions. Briefings
in Bioinformatics, 22(3): bbaa068, May 2021. https://doi.org/10.1093/bib/bbaa068
88.
Xinjie
Wang, Yaochu Jin, and Kuangrong Hao.
Synergies
between synaptic and intrinsic plasticity in echo state networks. Neurocomputing, 432: 32-43, 2021
89.
Hangyu
Zhu, Haoyu Zhang, and Yaochu Jin. From
federated learning to federated neural architecture search: A survey. Complex & Intelligent Systems,
7:639–657, 2021
90.
Pengfei
Huang, Handing Wang, and Yaochu Jin.
Offline
data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation,
60:100800, 2021
91.
Hao
Wang, Chaoli Sun, Guochen Zhang, Jonathan E. Fieldsend, and Yaochu Jin. Non-dominated
sorting on performance indicators for evolutionary many-objective optimization.
Information Sciences, 551:23-38, 2021
92.
Qian
Zhang, Jie Lu, and Yaochu Jin. Artificial
intelligence in recommender systems. Complex
& Intelligent Systems, 7:439–457, 2021
93. Sampo
Kuutti,
94. Haoyu Zhang, Yaochu
Jin, Ran Cheng, and Kuangrong Hao. Efficient evolutionary
search of attention convolutional networks via sampled training and node
inheritance. IEEE Transactions on
Evolutionary Computation, 25(2): 371 – 385, 2021
95. Hangyu Zhu
and Yaochu Jin. Toward real-time
federated evolutionary neural architecture search. In: N. Pillay and R. Qu
(eds.), Automated Design of Machine
Learning and Search Algorithms, Natural Computing Series, Springer, 2021. https://doi.org/10.1007/978-3-030-72069-8_8
96. Peng Liao,
Chaoli Sun, Guochen Zhang and Yaochu Jin.
Multi-surrogate
multi-tasking optimization of expensive problems. Knowledge-Based Systems, 551: 23-38, 2021
97. Handing
Wang, Liang Feng, Yaochu Jin, John
Doherty. Surrogate-assisted
evolutionary multitasking for expensive minimax optimization in multiple
scenarios. IEEE Computational
Intelligence Magazine, 16(1): 34-48, 2021
98. Guo
Yu, Yaochu Jin, and Markus Olhofer. A multi-objective
evolutionary algorithm for finding knee regions using two localized dominance
relationships. IEEE Transactions on
Evolutionary Computation, 25(1):145-158, 2021 Code available
at GitHub
99. Ye Tian,
Tao Zhang, Jianhua Xiao, Xingyi Zhang, and Yaochu
Jin. A
coevolutionary framework for constrained multi-objective optimization problems.
IEEE Transactions on Evolutionary
Computation, 25(1):102-116, 2021
100.Shuai Wang,
Jing Liu and Yaochu Jin. Finding influential nodes
in multiplex networks using a memetic algorithm. IEEE Transactions on Cybernetics, 51(2): 900-912, 2021
101.Yicun Hua, Qiqi Liu, Kuangrong Hao, and Yaochu Jin. A
survey of evolutionary algorithms for multi-objective optimization problems
with irregular Pareto fronts. IEEE/CAA
Journal of Automatica Sinica, 8(2): 303-318, 2021
102.Lucas
Z. Bissaro, Yaochu Jin, and Murillo
G. Carneiro. Regular echo state networks: simple and accurate reservoir models
to real-world applications. SAC 2021:
1063-1069
103.Ye Tian, Shichen Peng, Xingyi Zhang, Tobias Rodemann,
Kay Chen Tan, and Yaochu Jin. A
recommender system for metaheuristic algorithms for continuous optimization
based on deep recurrent neural networks. IEEE Transactions on Artificial Intelligence, 1(1):5-18, 2020
104.Li Huang,
Yongsheng Ding, Mengchu Zhou, Yaochu Jin,
and Kuangrong Hao. Multiple-solution
optimization strategy for multirobot task allocation. IEEE Transactions on Systems, Man, and Cybernetics: Systems,
50(11): 4283-4294, 2020
105.Yang Chen,
Xiaoyan Sun, and Yaochu Jin. Communication-efficient
federated deep learning with layer-wise asynchronous model update and
temporally weighted aggregation. IEEE
Transactions on Neural Networks and Learning Systems. 31(10): 4229 – 4238,
2020
Code here.
106.Shuai Wang,
Jing Liu and Yaochu Jin. Surrogate-assisted robust
optimization of large-scale networks based on graph embedding. IEEE Transactions on Evolutionary
Computation, 24(4): 735-749, 2020
107.Yicun Hua, Yaochu Jin, Kuangrong Hao, and Yuan
Cao. Generating
multiple reference vectors for a class of many-objective optimization problems
with degenerate Pareto fronts. Complex
& Intelligent Systems, 6(2): 275–285, 2020
Matlab code here
108.Ye Tian,
Xiutao Zheng, Xingyi Zhang, and Yaochu
Jin. Efficient
large-scale multi-objective optimization based on a competitive swarm optimizer.
IEEE Transactions on Cybernetics,
50(8):3696-3708, 2020
109.Guo
Yu, Yaochu Jin, and Markus Olhofer. Benchmark problems and
performance indicators for search of knee points in multi-objective
optimization. IEEE Transactions on
Cybernetics, 50(8): 3531-3544, 2020
Java
code here
110.Yan Zhou, Yaochu Jin, and Jinliang Ding. Surrogate-assisted
evolutionary search of spiking neural architectures in liquid state machines.
Neurocomputing, 406: 12-23, 2020
111.Yuanjun
Huang, Yaochu Jin, Kuangrong Hao. Decision-making
and multi-objectivization for cost sensitive robust optimization over time.
Knowledge-Based Systems, 199: 105857,
2020
112.Yang Chen, Yaochu Jin, Xiaoyan Sun. Language
model based interactive estimation of distribution algorithm. Knowledge-Based Systems, 200: 105980, 2020
113.Handing
Wang, Yaochu Jin, Cuie Yang, and
Licheng Jiao. Transfer
stacking from low- to high-fidelity: A surrogate-assisted bi-fidelity
evolutionary algorithm. Applied Soft
Computing, 92: 106276, 2020
114.Guoxia Fu,
Chaoli Sun, Ying Tan, Guochen Zhang, and Yaochu
Jin. A surrogate-assisted evolutionary algorithm with random feature
selection for large-scale expensive problems. Parallel Problem Solving from Nature, September 2020, Leiden, The
Netherlands
115.Cheng He, Ye
Tian, Handing Wang, and Yaochu Jin. A
repository of real-world datasets for data-driven evolutionary multiobjective
optimization. Complex &
Intelligent Systems, 6:189–197, 2020
116.Cuie Yang,
Jinliang Ding, Yaochu Jin, Tianyou
Chai. Off-line
data-driven multi-objective optimization: Knowledge transfer between surrogates
and generation of final solutions. IEEE
Transactions on Evolutionary Computation, 24(3):409-423, 2020
117.Shuai Wang,
Jing Liu, and Yaochu Jin. Robust structural
balance in signed networks using a multiobjective evolutionary algorithm. IEEE Computational Intelligence Magazine,
15(2):24-35, 2020
118.Yuanchao
Liu, Jianchang Liu, Yaochu Jin, Fei
Li, Tianzi Zheng. An
affinity propagation clustering based particle swarm optimizer for dynamic
optimization. Knowledge-Based Systems,
195: 105711, 2020
119.Dujuan
Wang, Yunqiang Yin, and Yaochu Jin. Rescheduling Under
Disruptions in Manufacturing Systems. Springer, Singapore, 2020
120.Hangyu Zhu
and Yaochu Jin. Multi-objective
evolutionary federated learning. IEEE
Transactions on Neural Networks and Learning Systems, 31(4): 1310-1322,
2020
121.Xinjie
Wang, Yaochu Jin and Kuangrong Hao. Evolving
local plasticity rules for synergistic learning in echo state networks. IEEE Transactions on Neural Networks and
Learning System, 31(4):1363-1374, 2020
122.Yanan Sun,
Handing Wang, Bing Xue, Yaochu Jin,
Gary G. Yen, and Mengjie Zhang. Surrogate-assisted evolutionary
deep learning using an end-to-end random forest-based performance predictor.
IEEE Transactions on Evolutionary
Computation, 24(2):350-364, 2020
123.Ye Tian,
Xingyi Zhang, Chao Wang, and Yaochu Jin.
An evolutionary
algorithm for large-scale sparse multi-objective optimization problems. IEEE Transactions on Evolutionary
Computation, 24(2):380-393, 2020
124.Ye
Tian, Xinyi Zhang, Ran Cheng, Cheng He, and Yaochu Jin. Guiding
evolutionary multi-objective optimization with generic front modeling. IEEE Transactions on Cybernetics, 50(3):
2168-2267, 2020
125.Xilu Wang, Yaochu Jin, Sebastian Schmitt, and
Markus Olhofer. An
adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective
optimization. Information Sciences,
519:317-331, 2020
126.Handing
Wang and Yaochu Jin. A random forest assisted
evolutionary algorithm for data-driven constrained multi-objective
combinatorial optimization of trauma systems. IEEE Transactions on Cybernetics, 50(2): 536-549, 2020
127.Xingyi
Zhang, Kefei Zhou, Hebin Pan, Lei Zhang, Xiangxiang Zeng, Yaochu Jin. A
network reduction based multi-objective evolutionary algorithm for community
detection in large-scale complex networks. IEEE Transactions on Cybernetics, 50(2): 703-716, 2020
128.Sutong
Wang, Yuyan Wang, Dujuan Wang, Yunqiang Yin, Yanzhang Wang, and Yaochu Jin. An
improved random forest-based rule extraction method for breast cancer diagnosis.
Applied Soft Computing, 86, 105941,
2020
129.Zhen Yang,
Yongsheng Ding, Yaochu Jin, and Kuangrong Hao. Immune-endocrine system
inspired hierarchical coevolutionary multiobjective optimization algorithm for
IoT service. IEEE Transactions on
Cybernetics, 50(1): 164-177, 2020
130.Xilu Wang, Yaochu Jin, Sebastian Schmitt, and
Markus Olhofer. Transfer learning for
Gaussian process assisted evolutionary bi-objective optimization for objectives
with different evaluation times. Genetic and Evolutionary Computation
Conference (GECCO 2020), 587–594, Cancun, Mexico, July 2020
Errata
(Corrections of the simulation results of an algorithm under comparison)
131.Rahma
Fourati, Boudour Ammar, Yaochu Jin
and Adel M. Alimi. EEG feature learning with intrinsic plasticity based deep
echo state network. International Joint
Conference on Neural Networks International Joint Conference on Neural Networks
(IJCNN 2020), Glasgow, UK, July 2020
132.Xinjie Wang, Yaochu
Jin and Kuangrong Hao. A gated recurrent unit based echo state network. International Joint Conference on Neural
Networks International Joint Conference on Neural Networks (IJCNN 2020), Glasgow,
UK, July 2020
133.Huaming
Chen, Yaochu Jin, Lei Wang, Chi-Hung
Chi and Jun Shen. HIME: Mining and ensembling heterogeneous information for
protein-protein interaction prediction. International
Joint Conference on Neural Networks (IJCNN 2020), Glasgow, UK, July 2020
134.Ye Tian,
Ran Cheng, Xingyi Zhang and Yaochu Jin.
Techniques for accelerating multi-objective evolutionary algorithms in PlatEMO.
Congress on Evolutionary Computation (CEC
2020), Glasgow, UK, July 2020
135.Cheng
He, Lianghao Li, Ye Tian, Xingyi Zhang, Ran Cheng, Yaochu Jin and Xin Yao. Accelerating large-scale
multi-objective optimization via problem reformulation. IEEE Transactions on Evolutionary
Computation, 23(6): 949 – 961,
2019
136.Cuie
Yang, Jinliang Ding, Yaochu Jin,
Chengzhi Wang, Tianyou Chai. Multi-tasking
multi-objective evolutionary operational indices optimization of beneficiation
processes. IEEE Transactions on
Automation Science and Engineering, 16(3):1046 – 1057, 2019
137.Zhen
Yang, Yaochu Jin, and Kuangrong Hao.
A bio-inspired
self-learning coevolutionary dynamic multiobjective optimization algorithm for
Internet of Things services. IEEE
Transactions on Evolutionary Computation, 23(4): 675 – 688, 2019
138.Fan Guo, Lihong Ren, Yaochu Jin, and Yongsheng Ding. A dynamic SVR–ARMA
model with improved fruit fly algorithm for the nonlinear fiber stretching
process. Natural Computing,
18(4): 735-746, 2019
139.Du-Juan Wang, Feng Liu and Yaochu Jin. A proactive scheduling approach to steel rolling process with
stochastic machine breakdown. Natural
Computing,
18(4):679-694 2019
140.Xin Ye, Jia Li, Sihao Liu, Jiwei Liang and Yaochu
Jin. A hybrid instance-intensive workflow scheduling method in private
cloud environment. Natural Computing, 18(4): 735-746, 2019
141.Huaming Chen, Lei Wang, Yaochu
Jin, Chi-Hung Chi, Fucun Li, Huaiyuan Chu,
and Jun Shen. Hyperparameters
estimation in SVM with GPU acceleration for prediction of protein-protein
interactions. IEEE BigData 2019.
142.Ye Tian,
Shichen Peng, Tobias Rodemann, Xingyi Zhang, and Yaochu Jin. Automated selection of
evolutionary multi-objective optimization algorithms. IEEE Symposium Series on Computational Intelligence, Xiamen, China,
December 2019
143.Jia Liu and
Yaochu Jin. Evolving hyperparameters
for training deep neural networks against adversarial attacks. IEEE Symposium Series on Computational
Intelligence, Xiamen, China, December
2019
144.Shufen Qin,
Chaoli Sun, Yaochu Jin and Guochen
Zhang. Bayesian approaches to
surrogate-assisted evolutionary multi-objective optimization: A comparative
study. IEEE Symposium Series on
Computational Intelligence, Xiamen, China, December 2019
145.Ye Tian,
Ran Cheng, Xingyi Zhang, Miqing Li, and Yaochu
Jin. Diversity
assessment of multi-objective evolutionary algorithms: Performance metric and
benchmark problems. IEEE
Computational Intelligence Magazine, 14(3): 61-74, 2019
146.Dong
Han, Wenli Du, Wei Du, Yaochu Jin
and Chunping Wu. An
adaptive decomposition-based evolutionary algorithm for many-objective
optimization. Information Sciences,
491: 204-222, 2019
147.Xinjie
Wang, Yaochu Jin, and Kuangrong Hao.
Echo
state networks regulated by local intrinsic plasticity rules for regression.
Neurocomputing, 351: 111-122, 2019
148.Xingguang
Peng, Yaochu Jin, and Handing Wang.
Multi-modal optimization
enhanced cooperative coevolution for large-scale optimization. IEEE Transactions on Cybernetics, 49(9):
3507-3520,
2019
149.Miao
Rong, Dunwei Gong, Yong Zhang, Yaochu
Jin, and Witold Pedrycz. Multi-directional
prediction approach for dynamic multi-objective optimization problems. IEEE Transactions on Cybernetics,
49(9):3362-3374, 2019
150.Yaochu Jin,
Handing Wang, Tinkle Chugh, Dan Guo, and Kaisa Miettinen. Data-driven evolutionary
optimization: An overview and case studies. IEEE Transactions on Evolutionary Computation, 23(3): 442-458,
2019
151.Jie
Tian, Ying Tan, Jianchao Zeng, Chaoli Sun, and Yaochu Jin. Multi-objective
infill criterion driven Gaussian process assisted particle swarm optimization
of high-dimensional expensive problems. IEEE
Transactions on Evolutionary Computation, 23(3):459 -472, 2019
152.Yicun
Hua, Yaochu Jin and Kuangrong Hao. A clustering based adaptive
evolutionary algorithm for multi-objective optimization with irregular Pareto
fronts. IEEE Transactions on
Cybernetics, 49(7):2758-2770, 2019
Matlab
code here (Note
that this code should be run within the PlatEMO Software tool) or here, which can run
independently.
153.Jinliang
Ding, Cuie Yang, Qiong Xiao, Tianyou Chai, and Yaochu Jin. Dynamic
evolutionary multi-objective optimization for raw ore allocation in mineral
processing. IEEE Transactions on
Emerging Topics in Computational Intelligence, 3(1): 36-48, 2019
154.Ye
Tian, Ran Cheng, Xingyi Zhang, Yansen Su, and Yaochu Jin. A
strengthened dominance relation considering convergence and diversity for
evolutionary many-objective optimization. IEEE Transactions on Evolutionary Computation, 23(2): 331
– 345, 2019
155.Handing
Wang, Yaochu Jin, Chaoli Sun and
John Doherty. Offline
data-driven evolutionary optimization using selective surrogate ensembles. IEEE Transactions on Evolutionary
Computation, 23(2):203-216, 2019
Matlab code in GitHub
156.Murillo.
G. Carneiro, Ran Cheng, Liang Zhao, Yaochu
Jin. Particle
swarm optimization for network-based data classification. Neural Networks, 110: 243-255, 2019
157.Tinkle
Chugh, Tomas Kratky, Kaisa Miettinen, Yaochu Jin, Pekka Makonen. Multiobjective shape
design in a ventilation system with a preference-driven surrogate-assisted
evolutionary algorithm. Proceedings of the Genetic and Evolutionary
Computation Conference, Pages 1147–1155, July 2019
158.Shufen Qin,
Chaoli Sun, Yaochu Jin, Lier Lan and
Ying Tan. A new selection strategy for decomposition-based evolutionary
many-objective optimization. IEEE
Congress on Evolutionary Computation, Wellington, New Zealand, June 2019
159.Hao Wang,
Chaoli Sun, Yaochu Jin, Shufen Qin
and Haibo Yu. A
Multi-indicator based Selection Strategy for Evolutionary Many-objective
Optimization. IEEE Congress on
Evolutionary Computation, Wellington, New Zealand, June 2019
160.Qiqi Liu, Yaochu
Jin, Martin Heiderich and Tobias Rodemann. Adaptation of reference
vectors for evolutionary many-objective optimization of problems with irregular
Pareto fronts. IEEE Congress on Evolutionary Computation, Wellington, New Zealand,
June 2019
161.Guo Yu, Yaochu Jin and Markus Olhofer. References or
preferences - rethinking many-objective evolutionary optimization. IEEE Congress on Evolutionary Computation,
Wellington, New Zealand, June 2019
162.Cheng He,
Ran Cheng, Yaochu Jin and Xin Yao. Surrogate-assisted
expensive many-objective optimization by model fusion. IEEE Congress on Evolutionary Computation, Wellington, New Zealand,
June 2019
163.Ye Tian,
Shangshang Yang, Xingyi Zhang and Yaochu
Jin. Using PlatEMO
to solve multi-objective optimization problems in applications: A case study on
feature selection. IEEE Congress on
Evolutionary Computation, Wellington, New Zealand, June 2019
164.Yan Zhou, Yaochu Jin and Jinliang Ding. Evolutionary
optimization of liquid state machines for robust learning. International Symposium on Neural Networks,
Moscow, Russia, July 10-12, 2019
165.Dan Guo, Yaochu
Jin, Jinliang Ding, and Tianyou Chai. Heterogeneous ensemble
based infill criterion for evolutionary multi-objective optimization of
expensive problems. IEEE Transactions
on Cybernetics, 49(3):1012-1025, 2019
166.Jinliang Ding, Cuie Yang, Yaochu Jin and Tianyou Chai. Generalized
multi-tasking for evolutionary optimization of expensive problems. IEEE Transactions on Evolutionary
Computation, 23(1): 44-58, 2019
167.Linqiang Pan, Cheng He, Ye Tian, Handing Wang, Xingyi
Zhang, and Yaochu Jin. A classification based
surrogate-assisted evolutionary algorithm for expensive many-objective
optimization. IEEE Transactions on
Evolutionary Computation, 23(1):74-88, 2019
168.Wei Du, Weimin Zhong, Yang Tang, Wenli Du and Yaochu Jin. High-dimensional robust
multi-objective optimization for order scheduling: A decision variable
classification approach. IEEE
Transactions on Industrial Informatics, 15(1): 293-304, 2019
169.Qinqin Fan, Yaochu
Jin, Weili Wang, and Xuefeng Yan. A
performance-driven multi-algorithm selection strategy for energy consumption
optimization of sea-rail intermodal transportation. Swarm and Evolutionary Computation, 44:1-17, 2019
170.Yuyan Han, Dunwei Gong, Yaochu Jin, and Quanke Pan. Evolutionary
multi-objective blocking lot-streaming flow shop scheduling with machine
breakdowns. IEEE Transactions on
Cybernetics, 49(1): 184-197, 2019
171.Yuyan
Wang, Dujuan Wang, Xin Ye, Yanzhang Wang, Yunqiang Yin, and Yaochu Jin. A
tree ensemble-based two-stage model for advanced-stage colorectal cancer
survival prediction. Information
Sciences, 474:106-124, 2019
172.Ruwang Jiao, Sanyou Zeng, Changhe Li, Yuhong Jiang and
Yaochu Jin. A
complete expected improvement criterion for Gaussian process assisted highly
constrained expensive optimization. Information
Sciences, 471, 80-96, 2019
173.Handing Wang, Yaochu
Jin and John Doherty. A
generic test suite for evolutionary multi-fidelity optimization. IEEE Transactions on Evolutionary
Computation. 22(6): 836 – 850, 2018
Matlab
code in GitHub
174.Shaoze Cui, Dujuan Wang, Yanzhang Wang, Pay-Wen Yu, Yaochu Jin. An improved
support vector machine-based diabetic readmission prediction. Computer Methods and Programs in Biomedicine,
166: 123-135, 2018
175.Ran Cheng, Cheng He, Yaochu Jin, and Xin Yao. Model-based
evolutionary algorithms – A short survey. Complex & Intelligent Systems, 4:283-292, 2018
176.Zhenping Xie, and Yaochu
Jin. An extended
reinforcement learning framework to model cognitive development with enactive
pattern representation. IEEE
Transactions on Cognitive and Developmental Systems, 10(3): 738-750, 2018
177.Fei Li, Ran Cheng, Jianchang Liu, and Yaochu Jin. TS-R2EA:
A two-stage R2 indicator based evolutionary algorithm for many-objective
optimization. Applied Soft Computing,
67: 245-260, 2018
178.Haibo Yu, Ying Tan, Jianchao Zeng, Chaoli Sun and Yaochu Jin. Surrogate-assisted
hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018
179.Zhaomin Chen, Chai Kiat Yeo, Bu Sung Lee, Chiew Tong
Lau and Yaochu Jin. Evolutionary
multi-objective optimization based ensemble autoencoders for image outlier
detection. Neurocomputing, 309:
192-200 2018
180.Chao Qian, Yu Yang, Ke Tang, Yaochu Jin, Xin Yao, and Zhi-Hua Zhou. On the
effectiveness of sampling for evolutionary optimization in noisy environments.
Evolutionary Computation, 26(2):237-267,
2018
181.Ye Tian, Ran Cheng, Xingyi Zhang, Fan Cheng, and Yaochu Jin. An indicator
based multi-objective evolutionary algorithm with reference point adaptation
for better versatility. IEEE
Transactions on Evolutionary Computation, 22(4): 609 - 622, 2018
Matlab code here
182.Chaoli Sun, Jinliang Ding, Jianchao Zeng and Yaochu
Jin. Fitness
approximation assisted competitive swarm optimizer for large scale expensive
optimization problems. Memetic Computing, 10(2):123-134 2018.
183.Chaoli Sun, Yaochu
Jin and Ying Tan. Semi-supervised
learning assisted particle swarm optimization of computationally expensive
problems. Genetic and Evolutionary
Computation Conference, pp.45-52, Kyoto, Japan, 15-19 July 2018
184.Guo Yu, Yaochu
Jin and Markus Olhofer. A method for a posteriori identification of knee
points based on solution density. Congress
on Evolutionary Computation, Rio de Janeiro, Brazil, 8-13 July 2018
185.Handing Wang, John Doherty and Yaochu Jin. Hierarchical
surrogate-assisted evolutionary multi-scenario airfoil shape optimization. Congress on Evolutionary Computation,
Rio de Janeiro, Brazil, 8-13 July 2018
186.Ye Tian, Xiaoshu Xiang, Xingyi Zhang, Ran Cheng and Yaochu Jin. Sampling reference points
on the Pareto fronts of multi-objective optimization problems. Congress on Evolutionary Computation,
Rio de Janeiro, Brazil, 8-13 July 2018
187.Xingyi Zhang, Ye Tian, Ran Cheng and Yaochu Jin.
A decision
variable clustering-based evolutionary algorithm for large-scale many-objective
optimization. IEEE Transactions on Evolutionary
Computation,
22(1):97-112, 2018 (“2020 IEEE TEVC Outstanding Paper Award”)
A draft here
Matlab code
for testing LMEA on LSMOP test suite.
MATLAB code for
tree-based ENS (T-ENS)
188.Tinkle Chugh, Yaochu Jin, Kaisa Miettinen,
Jussi Hakanen, and Karthink Sindhya. A
surrogate-assisted reference vector guided evolutionary algorithm for
computationally expensive many-objective optimization. IEEE Transactions on Evolutionary Computation, 21(1): 129-142, 2018
A draft here.
189.Hyondong Oh, Ataollah R. Shiraz, Yaochu Jin. Morphogen diffusion algorithms for tracking and herding using a
swarm of Kilobots. Soft Computing, 22(6): 1833-1844, 2018
190.Shenkai Gu, Ran Cheng, Yaochu Jin. Feature selection for high dimensional classification using a
competitive swarm optimizer. Soft
Computing,
22(3): 811-822, 2018
Java code here.
191.Xingyi Zhang, Xiutao Zheng, Ran Cheng, Jianfeng Qiu,
and Yaochu Jin. A
competitive mechanism based multi-objective particle swarm optimizer with fast
convergence. Information Sciences,
427:63-76,2018
Matlab code
here.
192.Ran Cheng, Yaochu Jin, Markus Olhofer and
Bernhard Sendhoff. Test problems for large-scale multiobjective and many-objective
optimization. IEEE Transactions on Cybernetics, 7(12): 4108-4121, 2017
A draft here
Source code for the
proposed test problems. Supplimentary
materials
193.Ataollah
Ramezan Shirazi and Yaochu Jin. A strategy for self-organized
coordinated motion of a swarm of minimalist robots. IEEE Transactions on Emerging Topics in Computational Intelligence,
1(5): 326 – 338, 2017
194.Ye Tian, Ran Cheng, Xingyi Zhang, and Yaochu Jin.
PlatEMO: A MATLAB platform for
evolutionary multi-objective optimization. IEEE Computational Intelligence Magazine, 12(4): 73-87, 2017 (“2019 IEEE CIM Outstanding Paper Award”)
195.Handing Wang, Markus Olhofer and Yaochu Jin. Mini-review
on preference modeling and articulation in multi-objective optimization:
Current status and challenges. Complex
& Intelligent Systems,
3(4): 233–245, 2017
196.Ye Tian, Handing Wang, Xingyi Zhang, and Yaochu Jin. Effectiveness
and efficiency of non-dominated sorting for evolutionary multi- and
many-objective optimization. Complex
& Intelligent Systems, 3(4): 247–263, 2017
197.Xin Ye, Sihao Liu, Yanli Yin and Yaochu Jin. User-oriented
many-objective cloud workflow scheduling based on an improved knee point driven
evolutionary algorithm. Knowledge
Based Systems,
135: 113-124, 2017
198.Tinkle Chugh, Nirupam Chakraborti, Karthik Sindhya,
and Yaochu Jin. A data-driven surrogate-assisted evolutionary algorithm applied to
a many-objective blast furnace optimization problem. Materials and Manufacturing Processes, 32(1): 1172-1178, 2017
199.Guangshun Yao,Yongsheng Ding, Yaochu Jin,
Kuangrong Hao. Endocrine-based
coevolutionary multi-swarm for multi-objective workflow scheduling in a cloud system.
Soft Computing, 21(15): 4309–4322, 2017
200.Murillo G. Carneiro, Thiago H. Cupertino, Ran Cheng, Yaochu
Jin and Liang Zhao. Nature-inspired
graph optimization for dimensionality reduction. The Annual IEEE International Conference on Tools with Artificial
Intelligence, November 6-7, 2017, Boston, MA, USA
201.Cheng He, Ye Tian, Yaochu Jin, Xingyi Zhang, and Linqiang Pan. A
radial space division based evolutionary algorithm for many-objective
optimization. Applied Soft Computing,
61:603-621, 2017
202.Handing Wang, Yaochu Jin, and John Doherty. Committee-based
active learning for surrogate-assisted particle swarm optimization of expensive
problems. IEEE Transactions on Cybernetics, 47(9): 2664-2677, 2017
Matlab
code in GitHub
203.Yiping Liu, Dunwei Gong, Jing Sun, and Yaochu Jin.
A
many-objective evolutionary algorithm using a one-by-one selection strategy.
IEEE Transactions on Cybernetics, 47(9): 2689-2702, 2017
204.Spencer Thomas, Yaochu
Jin, Josephine Bunch and Ian Gilmore. Enhancing classification of
mass spectrometry imaging data with deep neural networks. IEEE Symposium Series on Computational
Intelligence, November 27-December 1, 2017, Hawaii, USA
205.Nitin Naik,
Paul Jenkins, Roger Cooke, David Ball, Arthur Foster, Yaochu Jin. Augmented windows fuzzy
firewall for preventing denial of service attack. FUZZ-IEEE 2017: 1-6
206.Jie Tian, Chaoli Sun, Haibo Yu, Ying Tan, Jianchao
Zeng and Yaochu Jin. Comparisons of different kernels in Kriging-assisted
evolutionary expensive optimization. IEEE Symposium
Series on Computational Intelligence, November 27-December 1, 2017, Hawaii,
USA
207.Chaoli Sun, Yaochu Jin, Ran Cheng, Jinliang
Ding and Jianchao Zeng. Surrogate-assisted
cooperative swarm optimization of high-dimensional expensive problems. IEEE
Transactions on Evolutionary Computation, 21(4):644-660, 2017
208.Joseph Chrol-Cannon, Yaochu Jin and Andre
Gruning. An efficient method for online detection of polychronous patterns
in spiking neural networks. Neurocomputing, 267:644-650, 2017
209.Xingyi Zhang, Fuchen Duan, Lei Zhang, Fan Cheng, Yaochu
Jin, Ke Tang. Pattern recommendation in
task oriented applications: A multi-objective perspective. IEEE Computational Intelligence Magazine, 12(3):43-53, 2017
210.Cuie Yang, Jinliang Ding, Kay Chen Tan, and Yaochu
Jin. Two-stage
assortative mating for multi-objective multifactorial evolutionary optimization.
The 56th IEEE Conference on Decision and Control, December 12-15, 2017, Melbourne, Australia
211.Tinkle Chugh, Karthik Sindhya, Kaisa Miettinen, Yaochu
Jin, Tomas Kratky, and Pekka Makkonen. Surrogate-assisted
evolutionary multiobjective shape optimization of an air intake ventilation
system. Congress on Evolutionary Computation, 1541-1548, June 2017 ("2017 CEC Best Student Paper Award")
A draft here.
212.Handing Wang, Yaochu Jin and Xin Yao. Diversity assessment in many-objective optimization. IEEE Transactions on Cybernetics, 40(6):1510-1522, 2017
A draft of the paper here.
Matlab code in GitHub.
213.Ran Cheng, Miqing Li, Ye Tian, Xingyi Zhang,
Shengxiang Yang, Yaochu Jin and Xin Yao. A benchmark test suite for evolutionary many-objective optimization.
Complex & Intelligent Systems , 3(1):67-81, 2017
214.Shenkai Gu and Yaochu Jin. Multi-train:
A semi-supervised heterogeneous ensemble classifier. Neurocomputing,
249:202-211, 2017
215.Jing Liu, Yaxiong Chi, Chen Zhu and Yaochu Jin.
A time series driven decomposed evolutionary optimization approach
for reconstructing large-scale gene regulatory networks based on fuzzy cognitive
maps. BMC Bioinformatics, 18:241, 2017. DOI: 10.1186/s12859-017-1657-1
216.Ran Cheng, Tobias Rodemann, Michael Fischer, Markus
Olhofer, and Yaochu Jin. Evolutionary many-objective optimization of hybrid electric vehicle
control: From general optimization to preference articulation. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(2):97-111, 2017
217.Hyondong Oh, Ataollah Ramezan Shirazi, Chaoli Sun, and
Yaochu Jin. Bio-inspired
self-organising multi-robot pattern formation: A review. Robotics and Autonomous Systems, 91:83-100, 2017
218.Wissam A. Albukhanajer, Yaochu Jin, Johann A.
Briffa. Classifier ensembles for image identification using multi-objective
Pareto features. Neurocomputing, 238:316-327, 2017.
A draft here.
219.Yuanjun Huang, Yongsheng Ding, Kuangrong Hao, Yaochu
Jin. A
multi-objective approach to robust optimization over time considering switching
cost. Information Sciences, 394:183-197, 2017
220.Du-Juan Wang, Feng Liu and Yaochu Jin. A multi-objective evolutionary algorithm guided by directed search
for dynamic scheduling. Computers
& Operations Research, 79:
279-290, 2017
221.Richard Allmendinger, Michael T. M. Emmerich, Jussi
Hakanen, Yaochu Jin, and Enrico Rigoni. Surrogate-assisted
multicriteria optimization: Complexities, prospective solutions, and business
case. Journal of Multi-Criteria Decision
Analysis, 24(1/2):5-24, 2017
222.Nitin Naik, Paul Jenkins, Roger Cooke, David Ball,
Arthur Foster, Yaochu Jin. Augmented windows fuzzy
firewall for preventing denial of service attack. FUZZ-IEEE 2017: 1-6
223.Handing Wang and Yaochu Jin. Efficient nonlinear
correlation detection for decomposed search in evolutionary multi-objective
optimization. Congress on Evolutionary Computation, 649-656, June 2017
224.Ricardo Cerri, Rodrigo Coelho Barros, Andre Carlos
Ponce de Leon Ferreira Carvalho and Yaochu Jin. Reduction strategies for hierarchical
multi-label classification in protein function prediction. BMC Bioinformatics,
17:373, 2016. DOI: 10.1186/s12859-016-1232-1.
225.Xingguang Peng, Kun Liu and Yaochu Jin. A dynamic optimization approach to the design of cooperative
coevolutionary algorithms. Knowledge-Based
Systems, 109: 174-186, 2016
226.Handing Wang, Yaochu Jin and Jan O. Jansen. Data-driven surrogate-assisted multi-objective evolutionary
optimization of a trauma system. IEEE
Transactions on Evolutionary Computation, 20(6): 939-952, 2016
A draft of the paper here
227.Craig Brown, Yaochu Jin, Matthew Leach and
Martin Hodgson. \mu JADE: Adaptive differential evolution with a small population.
Soft Computing, 20(10): 4111-4120, 2016
A draft here.
228.Xingyi Zhang, Ye Tian, Yaochu Jin. Approximate non-dominated sorting for evolutionary many-objective
optimization. Information Sciences, 369:14-33, 2016
Source code of the aproximate sorting algorithm
(A-ENS) here, and the code of KnEA
using A-ENS and ENS
229.Ran Cheng, Yaochu Jin, Markus Olhofer and
Bernhard Sendhoff. A
reference vector guided evolutionary algorithm for many-objective optimization.
IEEE Transactions on Evolutionary Computation, 20(5):773-791, 2016
A draft of the paper is here; MATLAB code for non-constrained optimization here and MATLAB code for RVEA for
constrained optimization here, and Java
code implemented by third party here.
230.Dan Guo, Tianyou Chai, Jinliang Ding, and Yaochu
Jin. Small data
driven evolutionary multi-objective optimization of fused magnesium furnaces.
IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
231.Jussi Hakanen, Tinkle Chugh, Karthik Sindhya, Yaochu
Jin, Kaisa Miettinen. Connections
of reference vectors and different types of preference information in
interactive multiobjective evolutionary algorithms. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
232.Jie Tian, Yin Tan, Chaoli Sun, Jianchao Zeng, and Yaochu
Jin. A self-adaptive
similarity-based fitness approximation for evolutionary optimization. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
233.Ufuk Yolcu, Yaochu Jin and Erol Egrioglu. An ensemble of single
multiplicative neuron models for probabilistic prediction. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
234.Xingyi Zhang, Ye Tian, Ran Cheng, and Yaochu Jin.
Empirical analysis of a
tree-based efficient non-dominated sorting approach for many-objective
optimization. IEEE Symposium on Computational
Intelligence,
Athens, Greece, December 2016
235.Haibo Yu, Chaoli Sun, Jianchao Zeng, Ying Tan and Yaochu
Jin. An adaptive
model selection strategy for surrogate-assisted particle swarm optimization
algorithm. IEEE Symposium on Computational
Intelligence,
Athens, Greece, December 2016
236.Yaochu Jin. Data Driven Evolutionary Optimization of Complex Systems: Big Data
Versus Small Data. Invited talk, Workshop
on Surrogte-Assisted Evolutionary Optimisation. Genetic and Evolutionary
Computation Conference (GECCO), July 20-24 2016, Denver, CO, USA
Also a Plenary Speech at 2016
World Congress on Computational Intelligence (WCCI 2016), July 24-29,
Vancouver, Canada
237.Shi Cheng, Bin Liu, Yuhui Shi, Yaochu Jin and Bin
Li. Evolutionary
Computation and Big Data: Key Challenges and Future Directions. DMBD 2016,
LNCS 9714, pp. 3-14, 2016
238.Mohd-Hanif Yusoff, Joseph Chrol-Cannon and Yaochu
Jin. Modeling neural plasticity in echo state networks for
classification and regression. Information
Sciences, 364-365:184-196, 2016
A draft here.
239.Tinkle Chugh, Karthik Sindhya, Kaisa Miettinen, Jussi
Hakanen and Yaochu Jin. On
constraint handling in surrogate-assisted evolutionary many-objective
optimization. Parallel Problem Solving from Nature
(PPSN), September 2016, Edinburgh,
Scotland
240.Murillo Carneiro, Liang Zhao, Ran Cheng and Yaochu
Jin. Network
structural optimization based on swarm intelligence for highlevel
classification. International Joint Conference on
Neural Networks,
July 2016, Vancouver, Canada
241.Cuie Yang, Jinliang Ding, Tianyou Chai and Yaochu
Jin. Reference point
based prediction for evolutionary dynamic multiobjective optimization. Congress on Evolutionary Computation, July 2016, Vancouver, Canada
242.Ye Tian, Xingyi Zhang, Ran Cheng and Yaochu Jin.
A multi-objective
evolutionary algorithm based on an enhanced inverted generational distance
metric. Congress on Evolutionary Computation, July 2016, Vancouver, Canada
243.Yuyan Han, Dunwei Gong, Yaochu Jin, Quan-ke
Pan. Evolutionary multi-objective blocking lot-streaming flow
shopscheduling with interval processing time. Applied Soft Computing, 42:229-245, 2016
244.Yongsheng Ding, Tao Zhang, Lihong Ren, Yaochu Jin,
Kuangrong Hao and Lei Chen. Immune-inspired self-adaptive collaborative control allocation for
multi-level stretching processes. Information
Sciences, 342:81-95, 2016
245.Xingyi Zhang, Ye Tian and Yaochu Jin. A
knee point driven evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 19(6):761-776, 2015.
A draft of the paper can be downloaded here and MATLAB code
here.
246.Ran Cheng, Yaochu Jin, Kaname Narukawa and Bernhard
Sendhoff. A multiobjective
evolutionary algorithm using Gaussian process based inverse modeling. IEEE Transactions on Evolutionary Computation, 19(6):761-856, 2015.
A draft of the paper is here and the MATLAB code here.
247.Wissam A. Albukhanajer, Johann A. Briffa and Yaochu
Jin. Evolutionary multi-objective image feature extraction in the
presence of noise. IEEE Transactions on Cybernetics, 45(9):1757-1768, 2015.
248.Du-Juan Wang, Feng Liu, Yan-Zhang Wang and Yaochu Jin.
A
knowledge-based evolutionary proactive scheduling approach in the presence of
machine breakdown and deterioration effect. Knowledge-Based Systems. 90:70-80, 2015.
Also a draft here.
249.Joseph Chrol-Cannon and Yaochu Jin. Learning structure of sensory inputs with synaptic plasticity leads
to interference. Frontiers in Computational
Neuroscience,
2015.doi: 10.3389/fncom.2015.00103
A draft here
250.Yan Wu, Yaochu Jin and Xiaoxiong Liu. A
directed search strategy for evolutionary dynamic multiobjective optimization.
Soft Computing, 19(11):3221-3235, 2015. A draft here
251.Bin Yang, Yongsheng Ding, Yaochu Jin, Kuangrong
Hao.Self-organized swarm robot for target search and trapping inspired
by bacterial chemotaxis. Robotics
and Autonomous Systems , 72: 83-92, 2015.
A draft here.
252.Shenkai Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining and Knowledge Discovery, 5(5): 234-245, 2015
253.Xingyi Zhang, Ye Tian, Ran Cheng, and Yaochu Jin.
An efficient
approach to non-dominated sorting for evolutionary multi-objective optimization.
IEEE Transactions on Evolutionary Computation, 19(2):201-213, 2015 (“2017
IEEE TEVC Outstanding Paper Award")
See also here,
Matlab code ENS_SS, ENS_BS and the NSGA-II
with ENS.
254.Tameera Rahman, Mana Mahapatra, Emma Laing and Yaochu
Jin. Evolutionary non-linear modelling for selecting vaccines against
antigenically-variable viruses. Bioinformatics, 31(6):834-840, 2015
255.Ran Cheng and Yaochu Jin. A
competitive swarm optimizer for large scale optimization. IEEE Transactions on Cybernetics, 45(2):191-205, 2015
See also here.
Download the (updated) MATLAB code here
or C code here.
256.Ran Cheng and Yaochu Jin. A social learning particle swarm optimization algorithm for
scalable optimization. Information Sciences, 291:43-60, 2015
See also here.
Download the Matlab code here or C
code here.
257.Chaoli Sun, Yaochu Jin, Jianchao Zeng and Yang
Yu. A two-layer surrogate-assisted particle swarm optimization
algorithm. Soft Computing, 19(6):1461-1475, 2015. Also here
258.Tan Zhang, Yaochu Jin, Yongsheng Ding and
Kuangrong Hao. A cytokine
network inspired cooperative control system for multi-stage stretching
processes in fiber production. Soft
Computing,
19(6):1523-1540, 2015
259.Ran Cheng, Markus Olhofer and Yaochu Jin. Reference vector based a
posteriori preference articulation for evolutionary multiobjective optimization.
Congress on Evolutionary Computation (CEC 2015). May 24-28, 2015, Sendai, Japan
260.Yanling Jin, Yongsheng Ding, Kuangrong Hao and Yaochu
Jin.
261.Yuanjun Huang, Yaochu Jin and Yongsheng Ding. New performance indicators
for robust optimization over time. Congress
on Evolutionary Computation (CEC 2015). May 24-28, 2015, Sendai, Japan
A draft here.
262.Wissam A. Albukhanajer, Yaochu Jin and Johann
Briffa. Trade-off
between computational complexity and accuracy in evolutionary image feature
extraction. Congress on Evolutionary Computation
(CEC 2015). May
24-28, 2015, Sendai, Japan
263.Ran Cheng, Yaochu Jin and Kaname Narukawa. Adaptive
reference vector generation for inverse model based evolutionary multiobjective
optimization with degenerate and disconnected Pareto fronts. The 8th Int. Conf. on Evolutionary Multi-Criterion Optimization
(EMO'2015), pp.127-140,
Guimar?es, Portugal. A draft here.
264.Zhi-Hua Zhou, Nitesh V. Chawla, Yaochu Jin, and
Graham J. Williams. Big
data opportunities and challenges: Discussions from data analytics perspectives.
IEEE Computational Intelligence Magazine, 9(4):62-74, 2014 A
draft here ("2016 IEEE CIM Outstanding
Paper Award".)
265.Shenkai Gu and Yaochu Jin. Generating diverse and
accurate classifier ensembles using multi-objective optimization. IEEE Symposium Series on Computational Intelligence, December 9-12, 2014, Orlando, Florida, USA
266.Joseph Chrol-Cannon and Yaochu Jin. Computational modeling of neural plasticity for self-organization
of neural networks. BioSystems, 125:43-54, 2014 Also here
267.Christopher Smith and Yaochu Jin. Evolutionary
multi-objective generation of recurrent neural network ensembles for time series
prediction. Neurocomputing, 143:302-311, 2014. Also here
268.Christopher Smith, John Doherty, and Yaochu Jin.
Convergence based prediction
surrogates for high-lift CFD optimization. In: Royal Aeronautical Society - Applied Aerodynamics Conference, Bristol, UK, 2014
269.Mohd-Hanif Yusoff and Yaochu Jin. Modeling neural plasticity
in Echo State Networks for time series prediction. 2014 UK Workshop on Computational Intelligence, Bradford, UK, 8 - 10 September 2014
270.Chao Qian, Yang Yu, Yaochu Jin and Zhi-Hua
Zhou. On
the effectiveness of sampling for evolutionary optimization in noisy
environments. Parallel Problem Solving from Nature, September 13-17, 2014 Ljubljana, Slovenia
271.Ataollah Ramezan Shirazi, Hyondong Oh and Yaochu
Jin. Morphogenetic self-organization of collective movement without
directional sensing. Advances in Autonomous Robotics
Systems, Lecture Notes in Computer Science,
Volume 8717, pp 139-150, 2014
272.Hyondong Oh and Yaochu Jin. Adaptive swarm robot region coverage using gene regulatory networks.
Advances in Autonomous Robotics Systems, Lecture Notes in Computer Science, Volume 8717, pp
197-208, 2014
273.Joseph Chrol-Cannon and Yaochu Jin. On the
correlation between reservoir metrics and performance for time series
classification under the influence of synaptic plasticity. PLOS ONE,
DOI: 10.1371/journal.pone.0101792, July 10, 2014.
274.Spencer A. Thomas and Yaochu Jin. Reconstructing gene regulatory networks: Where
optimization meets big data. Evolutionary
Intelligence,
7(1):29-47, 2014
275.Aimin Zhou, Yaochu Jin and Qingfu Zhang. A population prediction
strategy for evolutionary dynamic multiobjective optimization. IEEE Transactions on Cybernetics, 44(1): 40-53, 2014
C++ code here.
276.Tong Liu, Chaoli Sun, Jianchao Zeng and Yaochu Jin.
Similarity- and
reliability-assisted fitness estimation for particle swarm optimization of
expensive problems. IEEE Congress on Evolutionary
Computation, July
2014, Beijing, China
277.Ran Cheng and Yaochu Jin. Demonstrator selection in a
social learning particle swarm optimizer. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
278.Hyondong Oh and Yaochu Jin. Evolving hierarchical gene
regulatory networks for morphogenetic pattern formation of swarm robotics. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
279.Wissam A. Albukhanajer, Yaochu Jin and Johann
A. Briffa. Neural
network ensembles for image identification using Pareto-optimal features. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
280.Christopher Smith, John Doherty and Yaochu Jin.
Multi-objective
evolutionary recurrent neural network ensemble for prediction of computational
fluid dynamic simulations. IEEE Congress
on Evolutionary Computation, July 2014, Beijing, China ( "Runner-up for the 2014 CEC Best Student Paper
Award".) here
281.Jiajia Chen, Yongsheng Ding, Yaochu Jin, and
Kuangrong Hao. A synergetic
immune clonal selection algorithm based multi-objective optimization method for
carbon fiber drawing process. Fibers
and Polymers,
14(10): 1722-1730, 2013
282.Lili Zhuang, Ke Tang and Yaochu Jin. Metamodel
assisted mixed-integer evolution strategies based on Kendall rank correlation
coefficient. The 14th International Conference
on Intelligent Data Engineering and Automated Learning (IDEAL'2013). October 20-23, 2013, Hefei, China
283.Ran Cheng and Yaochu Jin. On the competition
mechanism of the competitive particle swarm optimizer. UK Workshop on Computational Intelligence, September 9-11, 2013
284.Spencer A. Thomas, Yaochu Jin, Emma Laing and
Colin P. Smith. Reconstructing
regulatory networks in Streptomyces using evolutionary algorithms. UK Workshop on Computational Intelligence, September 9-11, 2013
285.Xiaoyan Sun, Dunwei Gong, Yaochu Jin, and
Shanshan Chen. A
new surrogate-assisted interactive genetic algorithm with weighted
semi-supervised learning. IEEE
Transactions on Cybernetics, 43(2):685-698, 2013
286.Spencer A. Thomas and Yaochu Jin. Evolving
connectivity between genetic oscillators and switches using evolutionary
algorithms. Journal of Bioinformatics and
Computational Biology,
Vol. 11, No. 3 (2013) 1341001 (15 pages)
287.Benjamin Inden, Yaochu Jin, Robert Haschke, Helger
Ritter, Bernhard Sendhoff. An examination of different fitness and novelty based selection
methods for the evolution of neural networks. Soft Computing.
17(5): 753-767, 2013.
288.Yaochu Jin, Ke Tang, Xin Yu, Bernhard Sendhoff and Xin Yao. A framework for finding robust optimal solutions over time. Memetic Computing,
5(1):3-18, 2013. A preprint here.
289.Mingh Nhgia Le, Yew Soon Ong, Stefan Menzel, Yaochu
Jin, and Bernhard Sendhoff. Evolution
by adapting surrogates. Evolutionary
Computation,
21(2):313-340, 2013
290.Ran Cheng, Chaoli Sun and Yaochu Jin. A multi-swarm evolutionary
framework based on a feedback mechanism. In: IEEE Congress on Evolutionary Computation (CEC'2013), Cancun, Mexico, June 20-23 2013
291.Ayang Xiao, Benli Wang and Yaochu Jin. Evolutionary truss layout
optimization using the vectorized structure approach. In: IEEE Congress on Evolutionary Computation (CEC'2013), Cancun, Mexico, June 20-23 2013
292.Jianfeng Lu, Bin Li, and Yaochu Jin. An
evolution strategy assisted by an ensemble of local Gaussian process models.
In: Genetic and Evolutionary Computation Conference
(GECCO'2013),
Amsterdam, The Netherlands, 6-10 July 2013
293.Christopher Smith, John Doherty, and Yaochu Jin.
Recurrent neural network
ensembles for convergence prediction in surrogate-assisted evolutionary
optimisation. IEEE Symposium on Computational
Intelligence in Dynamic and Uncertain Environments, part of the IEEE
Symposium Series on Computational Intelligence, Singapore, 16-19 April 2013
294.Chaoli Sun, Jianchao Zeng, Jengshyang Pan and Yaochu
Jin. Similarity
based evolution control for fitness estimation in particle swarm optimisation.
IEEE Symposium on Computational Intelligence in
Dynamic and Uncertain Environments, part of the IEEE Symposium Series on
Computational Intelligence, Singapore, 16-19 April 2013
295.Guanbo Jia, Yong Wang, Zixin Cai, and Yaochu Jin.
An improved (mu+lambda)-constrained differential evolution for
constrained optimization. Information
Sciences, 222:302-322, 2013
296.Yan Meng, Hongliang Guo and Yaochu Jin. A morphogenetic approach to flexible and robust shape formation for
swarm robotic systems. Robotics and Autonomous Systems, 61(1):25-38, 2013
297.Chaoli Sun, Jianchao Zeng, Jengshyang Pan, Songdong
Xue, Yaochu Jin. A new fitness estimation strategy for particle swarm optimization.
Information Sciences, 221:355-370, 2013
298.Spencer A. Thomas and Yaochu Jin. Single and multi-objective in silico evolution of tunable genetic
oscillators. The 7th Int. Conf. on Evolutionary
Multi-Criterion Optimization (EMO 2013), Sheffield, UK, March 2013. Also here.
299.Wissen A. Albukhanajer, Yaochu Jin, Johann A.
Briffa, and Godfried Williams. A
comparative study of multi-objective evolutionary Trace Transform algorithms
for robust feature extraction. The
7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO 2013), 19-22 March 2013, Sheffield, UK
300.Jun Yin, Yan Meng and Yaochu Jin. A developmental approach to structural self-organization in
reservoir computing. IEEE Transactions on Autonomous
Mental Development,
4(4):273-289, 2012
301.Lisa Schramm, Yaochu Jin, and Bernhard Sendhoff. Evolutionary Synthesis and Analysis of a Gene Regulatory Network
for Dynamically Stable Growth and Regeneration. Artificial Life, 18(4):425-444,
2012. Also here
302.Daniel Bush and Yaochu Jin. Calcium control
of hippocampal STDP. Journal of Computational Neuroscience. 33(3):495-514, 2012
303.Shenkai Gu and Yaochu Jin. Heterogeneous
classifier ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012
304.Yaochu Jin, Hongliang Guo, and Yan Meng. A hierarchical gene regulatory network for adaptive multi-robot
pattern formation. IEEE Transactions on Systems, Man,
and Cybernetics, Part B: Cybernetics, 42(3):805-816, 2012. See also here
for a draft.
305.Hongliang Guo, Yaochu Jin, and Yan Meng. A morphogenetic framework
for self-organized multi-robot pattern formation and boundary coverage. ACM Transactions on Autonomous and Adaptive Systems, Volume 7 Issue 1, Article No. 15, April 2012.
Doi:10.1145/2168260.2168275
306.Benjamin Inden, Yaochu Jin, Robert Haschke, Helge
Ritter. Evolving
neural fields for problems with large input and output spaces. Neural Networks,
28:24-39, 2012
307.Wissam Albukhanajer, Yaochu Jin, Johann Briffa
and Godfried Williams. Evolutionary
multi-objective optimization of Trace transform for invariant feature
extraction. 2012 IEEE Congress on Evolutionary
Computation,
Brisbane, Australia, June 2012
308.Joseph Chrol-Cannon, Andre Gruning and Yaochu Jin.
The emergence of polychronous groups under varying input patterns, plasticity
rules and network connectivities. 2012
International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, June 2012
309.Spencer A. Thomas and Yaochu Jin. Combining genetic oscillators and switches using
evolutionary algorithms. 2012
IEEE Symposium on Computational Intelligence in Bioinformatics and
Computational Biology, San
Diego, USA, May 2012
310.Lisa Schramm, Yaochu Jin and Bernhard Sendhoff. Quantitative
analysis of redundancy in evolution of developmental systems. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and
Computational Biology, San
Diego, USA, May 2012
311.Minh Nghia Le, Yew Soon Ong, Yaochu Jin and
Bernhard Sendhoff. A
unified framework for symbiosis of evolutionary mechanisms with application to
water clusters potential model design. IEEE
Computational Intelligence Magazine, 7(1): 20-35, 2012 (“2014 IEEE CIM Outstanding Paper Award".)
312.Yan Meng, Yaochu Jin and Jun Yin. Modeling activity-dependent plasticity in BCM spiking neural
networks with application to human behavior recognition. IEEE Transactions on Neural Networks, 22(12):1952-1966, 2011. See also here for a preprint.
313.Eva Gehrmann, Christine Glaesser, Yaochu Jin,
Bernhard Sendhoff, Barbara Drossel, and Kay Hamacher. Robustness of glycolysis in yeast to internal and external noise.
Physical Review E, E 84, 021913, 2011
314.Yaochu Jin and Yan Meng. Reply and Summary:
Evolutionary Developmental Robotics: The Next Step to Go? Newsletter of the Autonomous Mental Development Technical Committee, Vol. 8, No 2, pp. 9-11, October 2011
315.Yaochu Jin and Yan Meng. Evolutionary Developmental
Robotics: The Next Step to Go? The
Newletter of the Autonomous Mental Development Technical Committee, Vol. 8, No 1, pp. 13-14, April 2011
316.Sanghoun Oh, Yaochu Jin and Moongu Jeon. Approximate models for constraint
functions in evolutionary constrained optimization. International Journal of Innovative Computing, Information and Control, 7(11):6585-6603, 2011
317.Yuyang Zhang, Yan Meng, Yaochu Jin. Object
recognition using a bio-inspired neuron model with bottom-up and top-down
pathways. Neurocomputing, 74(17): 3158-3169, 2011. See also a preprint here.
318.Benjamin Inden, Yaochu Jin, Robert Haschke, and
Helge Ritter. Evolution
of multisensory integration in large neural fields. Artificial Evolution, 24-26 October 2011, Angers, France
319.Benjamin Inden, Yaochu Jin, Robert Haschke and
Helge Ritter. Exploiting inherent regularity in control of multilegged robot
locomotion by evolving neural fields. Third
World Congress on Nature and Biologically Inspired Computing (NaBIC2011), October 19-21, 2011, Salamanca University, Spain
320.Daniel Bush, Yaochu Jin. A unified
computational model of the genetic regulatory networks underlying synaptic,
intrinsic and homeostatic plasticity. BMC
Neuroscience,
12(Suppl 1):P161, 2011
321.Yaochu Jin. Surrogate-assisted
evolutionary computation: Recent advances and future challenges. Swarm and Evolutionary Computation, 1(2):61-70, 2011 (Invited survey paper). A preprint version here.
322.Yan Meng and Yaochu Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems. Springer, 2011
323.Lilian Tang, Tunde Peto, Jonathan Goh, Yaochu Jin,
C. Chuluunkhuu. Filtering Normal Diabetic Retinopathy Images through
Evolutionary Computation. European Journal of Ophthalmology, 21(3):347-348, 2011
324.Meiqin Liu, Senlin Zhang and Yaochu Jin. Multi-sensor
optimal H∞ fusion filters for delayed nonlinear intelligent systems based
on a unified model. Neural Networks, 24(3):280-290, 2011
325.Daniel Bush and Yaochu Jin, A unified computational
model of the genetic regulatory networks underlying synaptic, intrinsic and
homeostatic plasticity. 2011 International Conference on
Wiring the Brain: Making Connections, April 12-15, 2011, County Wicklow, Ireland (oral presentation)
326.Yaochu Jin and Yan Meng. Morphogenetic robotics: An emerging new field in developmental
robotics. IEEE Transactions on Systems, Man,
and Cybernetics, Part C: Applications and Reviews, 41(2):145-160, 2011. A preprint version here.
327.Yan Meng, Yuyang Zhang, and Yaochu Jin. Autonomous self-reconfiguration of modular robots by evolving a
hierarchical mechanochemical model. IEEE
Computational Intelligence Magazine, 6(1):43-54, 2011. See a preprint here.
328.Yaochu Jin and Yan Meng. Emergence
of robust regulatory motifs from in silico evolution of sustained
oscillation. BioSystems, 103(1): 38-44, 2011. A prteprint version here.
329.Lisa Schramm, Yaochu Jin and Bernhard Sendhoff. Redundancy
creates opportunity in developmental representations. 2011 IEEE Symposium on Artificial Life, Paris, France, April 11-15, 2011
330.Hongliang Guo, Yan Meng, and Yaochu Jin. Swarm robot pattern
formation using a morphogenetic multi-cellular based self-organization
algorithm. 2011 IEEE International Conference
on Robotics and Automation (ICRA 2011), Shanghai, China, May 9-13, 2011
331.Yan Meng, Yuyang Zhang, Abhay Sampath, Yaochu Jin,
and Bernhard Sendhoff. Cross-ball:
A new morphogenetic self-reconfigurable modular robot. 2011 IEEE International Conference on Robotics and Automation (ICRA
2011), Shanghai, China, May 9-13, 2011
332.Jonanthan Goh, Lilian Tang, L. Al Turk, Yaochu Jin,
Saleh, G., A combined particle swarm optimisation and genetic algorithm for
context analysis of medical images. In: 4th
International Conference on Health Informatics. Rome, Italy, 26-29 January, 2011
333.Yaochu Jin, Yan Meng, Hongliang Guo. A Morphogenetic Self-Organization Algorithm
for Swarm Robotic Systems using Relative Position Information. UK Workshop on Computational Intelligence. Colchester, September 8-10, 2010
334.Yan Meng and Yaochu Jin. Distributed multi-agent
systems for a collective construction task based on virtual swarm intelligence.
International Journal of Swarm Intelligence Research, 1(2), 58-79, 2010
335.Lisa Schramm, Vander Valente Martins, Yaochu Jin,
Bernhard Sendhoff. Analysis
of gene regulatory network motifs in evolutionary development of multi-cellular
organisms. Artificial Life XII, pp. 133-140, Odense, Denmark, August 2010
336.Yan Meng, Yuyang Zheng and Yaochu Jin. A
Morphogenetic Approach to Self-Reconfigurable Modular Robots using a Hybrid
Hierarchical Gene Regulatory Network. Artificial
Life XII, pp. 765-772, Odense, Denmark,
August 2010
337.Ben Jones, Yaochu Jin, Bernhard Sendhoff, and Xin
Yao. Emerged optimal distribution of computational
workload in the evolution of an undulatory animat. The 11th International Conference on Simulation of Adaptive Behaviors
(SAB 2010),
August 24-28, 2010
338.Yaochu Jin, Sanghoun Oh and Moongu Jeon. Incremental approximation of nonlinear
constraint functions for evolutionary constrained optimization. Congress on Evolutionary Computation, pp.2966-2973, Barcelona, July 2010
339.Xin Yu, Yaochu Jin, Ke Tang, and Xin Yao. Robust optimization over time -- A new
perspective on dynamic optimization problems. Congress on Evolutionary Computation, pp. 3998-4003, Barcelona, July 2010
340.Yan Meng, Yaochu Jin, Jun Yin, and Matthew
Conforth. Human activity
detection using spiking neural networks regulated by a gene regulatory network.
International Joint Conference on Neural Networks
(IJCNN), pp.2232-2237, Barcelona, July 2010
341.Hongliang Guo, Yan Meng, and Yaochu Jin. Analysis of local
communication load in shape formation of a distributed morphogenetic swarm
robotic system. Congress on Evolutionary Computation
(CEC), pp.1117-1124, Barcelona, July 2010
342.Yuhua Zheng, Yan Meng and Yaochu Jin. Fusing
bottom-up and top-down pathways in neural networks for visual object
recognition. International Joint Conference on
Neural Networks (IJCNN), pp.
2064-2031, Barcelona, July 2010
343.Till Steiner, Bernhard Sendhoff, and Yaochu Jin. Evolving heterochrony
for cellular differentiation using vector field embryogeny. Genetic and Evolutionary Computation Conference (GECCO), pp.571-578, Portland, July 2010
344.Benjamin Inden, Yaochu Jin, Robert Haschke, Helge
Ritter. NEATfields: Evolution
of neural fields for visual discrimination and multiple pole balancing tasks.
Genetic and Evolutionary Computation Conference
(GECCO), pp.645-646, Portland, 2010
345.Heiko Lex, Matthias Weigelt, Yaochu Jin, and
Thomas Schack. Visuo-motor adaptation relies on kinesthetic representation of
movement directions. North American Society for
Psychology of Sport and Physical Activity (NASPSPA) Conference, Tucson, AZ, June 10-12, 2010 (abstract only)
346.Dudy Lim, Yaochu Jin, Yew-Soon Ong, and
Bernhard Sendhoff. Generalizing surrogate-assisted evolutionary computation. IEEE Transactions on Evolutionary Computation, 14(3):329 - 355, 2010. A preprint version here.
347.Yaochu Jin and Jens Trommler. A fitness-independent evolvability measure for
evolutionary developmental systems. IEEE
Symposium on Computational Intelligence in Bioinformatics and Computational
Biology, pp.69-76, Montreal, Canada, May
2-5 2010 PDF ( “2010 CIBCB Best Paper Award”)
348.Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS
ONE, 4(12): e8177.
doi:10.1371/journal.pone.0008177, 2009
349.Ben Jones, Yaochu Jin, Bernhard Sendhoff, and
Xin Yao. The effect of proprioceptive feedback on the distribution of sensory
information in a model of an undulating organism. 10th European Conference on Artificial Life, Budapest, September 2009 (accepted)
350.Lisa Schramm, Yaochu Jin, Bernhard Sendhoff. Emerged coupling of motor control and morphological
development in evolution of multi-cellular animates. 10th European Conference on Artificial Life, Budapest, September 2009 (accepted)
351.Andrea Finke, Yaochu Jin, Helge Ritter. A P300 based brain-robot interface for shaping human-robot
interaction. Frontiers in Computational
Neuroscience, Conference Abstract:Bernstein Conference on Computational Neuroscience, doi: 10.3389/conf.neuro.10.2009.14.108, 2009 (oral
presentation)
352.Ben Jones, Yaochu Jin, Bernhard Sendhoff, and
Xin Yao. The evolutionary emergence of neural organization in a hydra-like
animat. Frontiers in Computational
Neuroscience, Conference Abstract:Bernstein Conference on Computational Neuroscience, doi: 10.3389/conf.neuro.10.2009.14.057, 2009
353.Hongliang Guo, Yan Meng, and Yaochu Jin. A cellular
mechanism for multi-robot construction via evolutionary multi-objective
optimization of a gene regulatory network. BioSystems, 98(3):193-203, 2009
354.Till Steiner, Yaochu Jin, Lisa Schramm, and
Bernhard Sendhoff. Dynamic
links and evolutionary history in simulated gene regulatory networks. In:
S. Das et al (eds.), Computational Methodologies in Gene
Regulatory Networks,
Chapter 21, pp. 498-522, 2009
355.Minh Nghia Le, Yew Soon Ong, Yaochu Jin, and
Bernhard Sendhoff.
Lamarkian memetic algorithms: Local optimum and connectivity structure
analysis. Memetic Computing, 1(3):175-190, 2009
356.Aimin Zhou, Qingfu Zhang, Yaochu Jin. Approximating the set of Pareto-optimal solutions in both decision
and objective spaces by an estimation of distribution algorithm. IEEE Transactions on Evolutionary Computation, 13(5):1167-1189, 2009
357.Yaochu Jin, Yan Meng, and Bernhard Sendhoff. Evolvability and robustness of in
silico evolution of gene regulatory dynamics. In: Foundations of Systems Biology in Engineering. Omnipress, pages 68--71, 2009
358.Yaochu Jin, Hongliang Guo and Yan Meng. Robustness analysis and
failure recovery of a bio-inspired self-organizing multi-robot system. In: Third IEEE International Conference on Self-Adaptive and Self-organizing
Systems. IEEE Press, pages 154--164, 2009
359.Yaochu Jin and Bernhard Sendhoff. A systems approach to evolutionary multi-objective structural
optimization and beyond. IEEE
Computational Intelligence Magazine, 4(3):62-76, 2009. Also available here
360.Yaochu Jin and Lipo Wang (editors), Fuzzy
Systems in Bioinformatics and Computational Biology. Springer, 2009
361.Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing
population and individual level of adaptation in changing environments. Adaptive Behavior,
17(2):153--174, 2009
362.Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto
analysis of evolutionary and learning systems. Frontiers of Computer Science in China, 3(1):4-17, 2009
363.Martijn Meeter, Rob Veldkamp, Yaochu Jin. Multiple
memory stores and operant conditioning: A rationale for memory's complexity.
Brain and Cognition, 69(1):200-208, 2009
364.Till Steiner, Jens Trommler, Martin Brenn, Yaochu Jin,
and Bernhard Sendhoff. Global shape with morphogen
gradients and motile polarized cells. Congress
on Evolutionary Computation, pp.2225-2232, May 2009, Trondheim, Norway
365.Yaochu Jin and Bernhard Sendhoff. Fuzzy logic in evolving in silico oscillatory
dynamics for gene regulatory networks. In: Y. Jin and L. Wang (eds.). Fuzzy Systems in Bioinformatics and Computational Biology, pp.315-327, Springer, 2009
366.Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff. Combination of genetic algorithms and evolution
strategies with self-adaptive switching. In: Goh, Chi-Keong; Ong, Yew-Soon;
Tan, Kay Chen (Eds.), Multi-Objective Memetic Algorithms. pp. 281-307,
Springer, 2009
367.Yaochu Jin, Yan Meng, Bernhard Sendhoff. Influence of
regulation logic on the easiness of evolving sustained oscillation for gene
regulatory networks. IEEE Symposium on Artificial Life
(IEEE-ALIFE),
pp.61-68, March 30 - April 1, 2009, Nashville, TN, USA
368.Yaochu Jin, Robin Gruna, Ingo Paenke, and Bernhard Sendhoff. Multi-objective optimization of
robustness and innovation in redundant genetic representations. IEEE Symposium on Multi-Criteria Decision-Making, pp.38-45, March 30 - April 1, 2009, Nashville, TN,
USA
369.Hongliang Guo, Yan Meng, Yaochu Jin. Self-adaptive
multi-robot construction using gene regulatory networks. IEEE Symposium on Artificial Life (IEEE-ALIFE), pp. 53-60, March 30 - April 1, 2009, Nashville, TN,
USA
370.Yaochu Jin, Lisa Schramm, and Bernhard Sendhoff. A gene regulatory model for the
development of primitive nervous systems. INNS-NNN Symposia on Modeling the Brain and Nervous Systems, November 2008, Auckland, New Zealand, LNCS 5506,
pp.48-55, 2009
371.Ben Jones, Yaochu Jin, Xin Yao, and Bernhard
Sendhoff. Evolution
of neural organization in a Hydra-like animat. 15th Int. Conf. on Neural Information Processing of the Asia-Pacific
Neural Network Assembly (ICONIP'08), November 2008, Auckland, New Zealand, LNCS 5506, pp. 216-223, 2009
372.Yaochu Jin, Bernhard Sendhoff. Pareto-based multi-objective machine learning: An overview and case
studies. IEEE Transactions on Systems, Man,
and Cybernetics, Part C: Applications and Reviews, 38(3):397-415, 2008. Also here.
373.Qingfu Zhang, Aimin Zhou, Yaochu Jin. RM-MEDA:
A regularity model based multiobjective estimation of distribution algorithm.
IEEE Transactions on Evolutionary Computation, 12(1):41--63, 2008. Also here.
( Errata:
Correction of Fig.20 )
374.Dudy Lim, Yew-Soon Ong, Yaochu Jin, and
Bernhard Sendhoff. Evolutionary optimization with dynamic fidelity
computational models. International Conference on
Intelligent Computing,
pp.235-242, LNAI 5227, September 15-18, 2008, Shanghai, China
375.Ben Jones, Yaochu Jin, Bernhard Sendhoff, and
Xin Yao. Evolving functional symmetry in a three dimensional model of an
elongated organism. Artificial Life XI, pp.305-312, 2008 PDF
376.Till Steiner, Yaochu Jin and Bernhard Sendhoff. A cellular model for evolutionary development of lightweight
materials with an inner structure. Genetic
and Evolutionary Computation Conference (GECCO), pp.851-858, 2008 ( “Shortlisted for Best Paper
Award”)
377.Yi Cao, Yaochu Jin, Michal Kowalczykiewicz and
Bernhard Sendhoff. Prediction of convergence dynamics of design performance
using differential recurrent neural networks. International Joint Conference on Neural Networks, pp.529-534, 2008, Hong Kong, China
378.Aimin Zhou, Qingfu Zhang, Yaochu Jin and Bernhard
Sendhoff. Combination of EDA and DE for continuous biobjective optimization. Congress on Evolutionary Computation, pp.1447-1454, 2008, Hong Kong, China
379.Neale Samways, Yaochu Jin, Xin Yao, and
Bernhard Sendhoff. Toward a gene regulatory network model for evolving
chemotaxis behaviour. Congress on Evolutionary Computation, pp.2574-2581, 2008, Hong Kong, China
380.Yaochu Jin, Bernhard Sendhoff. Evolving in
silico bistable and oscillatory dynamics
for gene regulatory network motifs. Congress
on Evolutionary Computation , pp.386-391, 2008, Hong Kong, China
381.Yaochu Jin, Bernhard Sendhoff, Edgar Körner. Rule extraction from compact Pareto-optimal neural networks. In: Multi-objective Evolutionary Algorithms for Knowledge Discovery from
Databases, A.
Ghosh et al (eds.), pp. 71-90, Springer, 2008
382.Yaochu Jin, Aimin Zhou, Qingfu Zhang, Bernhard Sendhoff, and Edward Tsang.
Modeling regularity to improve scalability of model-based multi-objective
optimization algorithms. In: J. Knowles, D. Corne, K. Deb (eds.), Multi-Objective
Problem Solving from Nature, pp. 331-356, Springer, 2008
383.Shengxiang Yang, Yew-Soon Ong, and Yaochu Jin
(editors) Evolutionary
Computation in Dynamic and Uncertain Environments , Springer, 2007
384.Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff,
Bu-Sung Lee. Efficient hierarchical parallel genetic algorithms using grid
computing. Future Generation Computer Systems
-- The International Journal of Grid Computing: Theory, Methods and
Applications.
23(4):658--670, 2007 PDF
385.Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard
Sendhoff. Adaptive
modeling strategy for continuous multi-objective optimization. Congress on Evolutionary Computation, pp.431--437, Singapore, September 2007 PDF
386.Till Steiner, Lisa Schramm, Yaochu Jin, Bernhard
Sendhoff. Emergence
of feedback in artificial gene regulatory networks. Congress on Evolutionary Computation, pp.867--874, Singapore, September 2007 ( 10 finalist for best
paper award)
Available upon request.
387.Yaochu Jin, Ruojing Wen, and Bernhard Sendhoff. Evolutionary
multi-objective optimization of spiking neural networks. International Conference on Neural Networks, LNCS 4668, 1:370--379, 2007 PDF
388.Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard
Sendhoff. A study on metamodeling techniques, ensembles, and multi-surrogates
in evolutionary computation. Genetic
and Evolutionary Computation Conference (GECCO), pp.1288--1295, July 8-11, 2007, London PDF
389.Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard
Sendhoff and Edward Tsang. Global multi-objective optimization via estimation
of distribution algorithm with biased initialization and crossover. Genetic and Evolutionary Computation Conference (GECCO), pp.617--623, July 8-11, 2007, London PDF
390.Ingo Paenke, Juergen Branke, and Yaochu Jin. On the influence of phenotype plasticity on genotype
diversity. 2007 IEEE Symposium on Foundations
of Computational Intelligence (FOCI) , pp. 33-40, April 1-4, 2007, Honolulu, Hawaii PDF
( “Best Student Paper Award”)
391.Aimin Zhou, Yaochu Jin, Qingfu Zhang, Bernhard
Sendhoff, Edward Tsang. Prediction-based population re-initialization for
evolutionary dynamic multi-objective optimization. The Fourth International Conference on Evolutionary Multi-Criterion
Optimization,
LNCS 4403, pp. 832--846, March 5-8, 2007, Matsushima, Japan. PDF
392.Dudy Lim, Yew-Soon Ong, Meng-Hiot Lim, and Yaochu
Jin. Single/multi-objective inverse robust evolutionary design methodology
in the presence of uncertainty. In: S. Yang, Y.S. Ong, and Y. Jin (eds.), Evolutionary Computation in Dynamic and Uncertain Environments, pp.437-456, Springer, 2007
393.Lars Graenling, Yaochu Jin, Bernhard Sendhoff. Individual-based management of meta-models for
evolutionary optimization with applications to three-dimensional blade
optimization. In: S. Yang, Y.S. Ong, and Y. Jin (eds.), Evolutionary Computation in Dynamic and Uncertain Environments, pp.225-250, Springer, 2007
394.Yaochu Jin (editor). Multi-Objective
Machine Learning. Springer, Berlin Heidelberg. 2006
395.Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard
Sendhoff, and Bu Sung Lee. Inverse
multi-objective robust evolutionary optimization. Genetic Programming and Evolvable Machines. 7(4):383--404, 2006 Also here
396.Ingo Paenke, Juergen Branke, and Yaochu Jin. Efficient
search for robust solutions by means of evolutionary algorithms and fitness
approximation. IEEE Transactions on Evolutionary
Computation . 10(4):405-420, 2006 ( Authors contributed equally.)
Also here.
397.Kwasi Foli, Tatsuya Okabe, Markus Olhofer, Yaochu Jin,
and Bernhard Sendhoff. Optimization
of micro heat exchanger: CFD, analytical approaches and multi-objective
evolutionary algorithms. International Journal of Heat and
Mass Transfer.
49:1090-1099, 2006
398.Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard
Sendhoff, Edward Tsang. Modeling the population distribution in multi-objective
optimization by generative topographic mapping. Parallel Problem Solving from Nature IX, LNCS 4193, pp.443-452, 2006, Reykjavik, Iceland PDF
399.Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard
Sendhoff. Trusted evolutionary algorithms. IEEE Congress on Evolutionary Computation, pp.456-463, July 2006, Vancouver
400.Lars Gräning, Yaochu Jin, Bernhard Sendhoff. Generalization improvement in multi-objective learning.
International Joint Conference on Neural Networks, pp.9893-9900, July 2006, Vancouver
401.Yaochu Jin, Bernhard Sendhoff. Alleviating catastrophic
forgetting via multi-objective learning. International Joint Conference on Neural Networks, pp.6367-6374, July 2006, Vancouver
402.Aimin Zhou, Yaochu Jin, Qingfu Zhang, Bernhard
Sendhoff, Edward Tsang. Combining model-based and
genetics-based offspring generation for multi-objective optimization using a
convergence criterion. IEEE Congress on Evolutionary
Computation,
pp.3234-3240, July 2006, Vancouver
403.Yaochu Jin, Bernhard Sendhoff, Edgar Körner. Simultaneous generation of accurate and interpretable neural network
classifiers. In: Multi-Objective Machine Learning, Y. Jin (ed.), pp.281-300, Springer, Berlin
Heidelberg, 2006
404.Lipo Wang and Yaochu Jin (editors), 2005 International Conference on Fuzzy Systems and Knowledge
Discovery. Part I and Part II, LNAI
3613 and 3614, Springer, August 2005
405.Rothlauf, F., Branke, J., Codnoni, S., Corne, D.W.,
Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romerero, J., Smith,
G.D., Squillero, G. (editors). Applications of Evolutionary Computing. LNCS 3449, Springer, March
2005
406.Yaochu Jin (editor). Knowledge Incorporation in Evolutionary Computation.
Springer, Berlin Heidelberg, 2005 Table of
Contents(PDF file)
407.Yaochu Jin and Juergen Branke. Evolutionary optimization in uncertain environments - A survey.
IEEE Transactions on Evolutionary Computation, 9(3), 303-317, 2005. Also here.
Citations
according to Google
Scholar
408.Hanli Wang, Sam Kwong, Yaochu Jin, Wei Wei and K.
Man. Agent-based
evolutionary approach to interpretable rule-based knowledge extraction. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications
and Reviews,
35(2), 143-155, 2005
409.Hanli Wang, Sam Kwong, Yaochu Jin, Wei Wei and K.
Man. A
multi-objective hierarchical genetic algorithm for interpretable rule-based
knowledge extraction. Fuzzy Sets and Systems, 149(1), 149-186, 2005
Citations
according to Google
Scholar
410.Yaochu Jin. A comprehensive survey of fitness approximation
in evolutionary computation. Soft
Computing, 9(1),
3-12, 2005, Springer
Citations
according to Google
Scholar
411.Michael Huesken, Yaochu Jin and Bernhard Sendhoff. Structure optimization of neural networks for evolutionary
design optimization. Soft Computing, 9(1), 21-28, 2005
412.Aimin Zhou, Qingfu Zhang, Yaochu Jin, Edward
Tsang, Tatsuya Okabe. A model-based evolutionary algorithm
for bi-objective optimization. Congress
on Evolutionary Computation, pp.2568-2575, Edinburgh, September 2005
413.Vineet Khare, Xin Yao, Bernhard Sendhoff, Yaochu
Jin, and Heiko Wersing. Co-evolutionary modular neural networks for automatic
problem decomposition. Congress on Evolutionary Computation, pp.2691-2698, Edinburgh, September 2005
414.Tatsuya Okabe, Yaochu Jin, and Bernhard Sendhoff. Theoretical comparisons
of search dynamics of genetic algorithms and evolution strategies. Congress on Evolutionary Computation, pp.382-389, Edinburgh, September 2005
415.Tatsuya Okabe, Yaochu Jin, and Bernhard Sendhoff. A new approach to
dynamics analysis of genetic algorithms without selection. Congress on Evolutionary Computation, pp.374-381, Edinburgh, September 2005
416.Yaochu Jin, Markus Olhofer, and Bernhard Sendhoff. On evolutionary optimization of
large problems with small populations. Int.
Conf. on Natural Computation. LNCS, 3611,
pp.1145-1154, Springer, Changsha, China
417.Lars Gräning, Yaochu Jin, Bernhard Sendhoff. Efficient evolutionary optimization using individual-based
evolution control and neural networks: A comparative study. European Symposium on Artificial Neural Networks (ESANN'2005). pp.273-278, Bruges, April 2005
418.Yaochu Jin, Bernhard Sendhoff, and Edgar Körner. Evolutionary multi-objective
optimization for simultaneous generation of signal-type and symbol-type
representations. The Third International Conference
on Evolutionary Multi-Criterion Optimization. LNCS
3410, pp.752-766, Springer, Guanajuato, Mexico, March 9-11, 2005
419.Yaochu Jin, Michael Huesken, Markus Olhofer and Bendhard Sendhoff. Neural networks for fitness approximation in
evolutionary optimization. In: Y. Jin (ed.), Knowledge Incorporation in Evolutionary Computation,, pp.281-306, Springer, Berlin Heidelberg, 2005
420.Raidl, G., Cagnoni, S., Branke, J., Corne, D.W.,
Drechsler, R., Jin, Y., Johnson, C.G., Machado, P., Marchiori, E.,
Rothlauf, F., Smith, G.D., Squillero, G. (editors).
Applications of Evolutionary Computing. LNCS 3005, Springer, April
2004
421.Yaochu Jin, Bernhard Sendhoff, and Edgar Körner. Evolutionary multi-objective model selection: A step
towards smooth transitions between signal-type and symbol-type representations? Workshop on "Soft Computing for Information Mining" within KI 2004, Ulm, September 20-21, 2004 (not
peer reviewed)
422.Tatsuya Okabe, Yaochu Jin, Markus Olhofer, and
Bernhard Sendhoff. On test functions for evolutionary multi-objective
optimization. Parallel Problem Solving from
Nature, VIII, LNCS 3242, Springer,
pp.792-802, September 2004
423.Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff and
Markus Olhofer. Voronoi-based estimation of distribution
algorithm for multi-objective optimization. CEC'04, pp.
1594-1602, Portland, 2004
424.Yaochu Jin, Tatsuya Okabe and Bernhard Sendhoff. Neural network regularization
and ensembling using multi-objective evolutionary algorithms. Congress on Evolutionary Computation, pp.1-8, Portland, 2004
Citations
according to Google
Scholar
425.Yaochu Jin and Bernhard Sendhoff. Reducing fitness evaluations
using clustering techniques and neural network ensembles.(draft) Genetic and Evolutionary Computation Conference. LNCS
3102, Springer, pp. 688-699, Seattle, 2004
Citations
according to Google
Scholar
426.Yaochu Jin and Bernhard Sendhoff. Constructing dynamic test
problems using the multi-objective optimization concept. In: Applications of Evolutionary Computing. LNCS
3005, Raidl, G.R.; Cagnoni, S.; Branke, J.; Corne, D.W.; Drechsler, R.; Jin,
Y.; Johnson, C.G.; Machado, P.; Marchiori, E.; Rothlauf, F.; Smith, G.D.;
Squillero, G. (eds.) pp.525-536, Springer, 2004
427.Yaochu Jin, Tatsuya Okabe and Bernhard Sendhoff. Evolutionary multi-objective approach to constructing
neural network ensembles for regression. In: C. Coello Coello (ed.), Applications of Evolutionary Multi-objective Optimization, pp. 653-672. World Scientific, 2004
428.Yaochu Jin. Advanced Fuzzy Systems Design and Applications . Physica-Verlag/Springer-Verlag, Heidelberg, 2003 (ISBN: 3-7908-1537-3)Table of Contents (PDF file).
429.Yaochu Jin and Bernhard Sendhoff, Extracting interpretable
fuzzy rules from RBF networks. Neural
Processing Letters,
17(2), 149-164, 2003
Citations
according to Google
Scholar
430.Yaochu Jin and Bernhard Sendhoff. Connectedness,
regularity and the success of local search in evolutionary multi-objective
optimization. In: Proceedings of the IEEE Congress on
Evolutionary Computation,
Vol.3, pp.1910-1917, 2003
431.Lars Willmes, Thomas Bäck,Yaochu Jin and
Bernhard Sendhoff. Comparing neural networks and
kriging in fitness approximation in evolutionary optimization. In: Proceedings of the IEEE Congress on Evolutionary Computation, Vol.1, pp.663-670, 2003
432.Tatsuya Okabe, Yaochu Jin and Bernhard Sendhoff. A critical survey
of performance indices for multi-objective optimization.In: Proceedings of the IEEE Congress on Evolutionary Computation, Vol.2, pp.878-885, 2003
Citations
according to Google
Scholar
433.Tatsuya Okabe, Kwasi Foli, Markus Olhofer, Yaochu Jin
and Bernhard Sendhoff. Comparative studies on micro heat exchanger
optimization. In: Proceedings of the IEEE Congress on
Evolutionary Computation,
Vol.1, pp.647-654, 2003
434.Tatsuya Okabe, Yaochu Jin and Bernhard Sendhoff. Evolutionary multi-objective
optimization with a hybrid representation.In: Proceedings of the IEEE Congress on Evolutionary Computation , Vol.4, pp. 2262-2269, 2003
435.Yaochu Jin, Tatsuya Okabe and Bernhard Sendhoff. Solving three-objective
optimization problems using evolutionary dynamic weighted aggregation: Results
and analysis. In: Proceedings of Genetic and
Evolutionary Computation Conference. pp.636, Chicago, 2003
436.Yaochu Jin and Bernhard Sendhoff. (Corrected version)
Trade-off between performance and robustness: An evolutionary multiobjective
approach. In: Proceedings of Second International
Conference on Evolutionary Multi-criteria Optimization. LNCS
2632, Springer, pp.237-251, Faro, April 2003
Citations
according to Google
Scholar
437.Yaochu Jin, Michael Huesken and Bernhard Sendhoff. Quality measures for approximate models in evolutionary
computation. In: Proceedings of the GECCO Workshop on
"Learning, Adaptation and Approximation in Evolutionary Computation", pp.170-174, Chicago, 2003 (not peer reviewed)
438.Yaochu Jin. Interpretability improvement of RBF-based neuro-fuzzy systems using
regularized learning. In: J. Cassilas et al (eds.), Interpretability Issues in Fuzzy Modeling, Chapter 26, pp.605-620, Springer, 2003
439.Yaochu Jin. Generating distinguishable, complete, consistent and compact fuzzy
systems using evolutionary algorithms. In: J. Cassilas et al (eds.), Accuracy Improvements in Fuzzy Modeling , Chapter 5, pp.100-118, Springer, 2003.
440.Yaochu Jin. Brain controlled devices - An overview. Internal Report, Honda
Research Institute Europe, HRI-EU 03-13, September, 2003
441.Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. A framework for evolutionary
optimization with approximate fitness functions. IEEE Transactions on Evolutionary Computation, 6(5), 481-494, 2002
Citations
according to Google
Scholar
442.Yaochu Jin and Bernhard Sendhoff. Fuzzy preference incorporation
into evolutionary multi-objective optimization. In: Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution
and Learning,
Vol.1, pp.26-30, Singapore, Nov. 2002
443.Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff. On the dynamics of multiobjective optimization. In: Proceedings of Genetic and Evolutionary Computation Conference, pp. 247-256, New York, July 2002. ( Best paper nomination)
444.Yaochu Jin. Fitness approximation in evolutionary computation
- A survey. In: Proceedings of Genetic and
Evolutionary Computation Conference, pp.1105-1112, New York, July 2002.
Citations
according to Google
Scholar
445.Yaochu Jin and Bernhard Sendhoff. Incorporation of fuzzy preferences into
evolutionary multiobjective optimization. In: Proceedings of Genetic and Evolutionary Computation Conference, pp.683, New York, July 2002.
446.Dissertation: Knowledge in evolutionary and learning systems. Institute for
Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002.
(ISBN: 3-8265-9749-4)
447.Markus Olhofer, Toshiyuki Arima, Yaochu Jin,
Toyotaka Sonoda and Bernhard Sendhoff. Optimization of transonic gas turbine
blades with evolution strategies. Honda
R&D Technical Review,
14(1), 203-216, 2002
448.Yaochu Jin. Knowledge in evolutionary and learning systems. Ph.D. thesis.
Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag,
Aachen, 2002. (ISBN: 3-8265-9749-4)
449.Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. Managing approximate models in evolutionary
aerodynamic design optimization. In: Proceedings
of IEEE Congress on Evolutionary Computation, vol.1, pp.592-599. Seoul, Korea, May 2001
Citations
according to Google
Scholar
450.Markus Olhofer, Yaochu Jin and Bernhard
Sendhoff. Adaptive encoding for aerodynamic shape optimization using evolution
strategies. In: Proceedings of IEEE Congress on
Evolutionary Computation,
vol.1, pp.576-583, Seoul, Korea, May 2001
451.Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. Dynamic weighted aggregation for
evolutionary multi-objective optimization: Why does it work and how? In: Proceedings of Genetic and Evolutionary Computation Conference, pp.1042-1049, San Francisco, USA, 2001.
Citations
according to Google
Scholar
A more detailed description with applications
can be found in the unpublished manuscript: Effectiveness of weighted sum
of the objectives for evolutionary multi-objective optimization: Methods,
analysis and applications. Unpublished manuscript. 2002
452.Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. Managing approximate models in parallel evolutionary
optimization. HRE-G/FTR Report 00-03, Honda R&D Europe, Offenbach/Main,
2000.
453.Yaochu Jin, Tatsuya Okabe and Bernhard Sendhoff. Adapting weighted aggregation for
multiobjective evolution strategies. In: Proceedings of the First International Conference on Evolutionary
Multi-criterion Optimization. LNCS 1993,
Springer, pp.96-110, Zurich, Switzerland, March 7-9, 2001.
Citations
according to Google
Scholar
454.Yaochu Jin. Fuzzy modeling of high-dimensional systems:
Complexity reduction and interpretability improvement. IEEE Transactions on Fuzzy Systems, 8(2), 212-221, 2000.
Highly cited article (top 1% within its field)
according to Essential Science Indicators (SM) of Thomson ISI
Citations
according to Google
Scholar
455.Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. On evolutionary optimization with
approximate fitness functions. In: Proceedings
of the Genetic and Evolutionary Computation Conference GECCO, Las Vegas, Nevada, USA. pp.786- 793, July 10-12,
2000.
456.Yaochu Jin, Werner von Seelen and Bernhard Sendhoff. Extracting Interpretable Fuzzy
Rules from RBF Neural Networks. Internal Report 2000-02, Institut für
Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany, February 2000.
457.Yaochu Jin and Bernhard Sendhoff. Knowledge incorporation
into neural networks from fuzzy rules. Neural
Processing Letters,
10(3), 231-242, 1999.
458.Yaochu Jin, Werner von Seelen and Bernhard Sendhoff. On generating FC3(flexible,
complete, consistent and compact) fuzzy rule systems from data using evolution
strategies. IEEE Transactions on Systems, Man
and Cybernetics,
Part B: Cybernetics, 29(6), 829-845, 1999.
Citations
according to Google
Scholar
459.Yaochu Jin and Werner von Seelen. Evaluating flexible fuzzy controllers via evolution strategies. Fuzzy Sets and Systems, 108, 243-252, 1999
Citations
according to Google
Scholar
460.Anna Buczak, Yaochu Jin, Houshang Darabi and
Mohsen Jafari. Genetic algorithm based sensor network
optimization for target tracking. Intelligent
Engineering Systems through Artificial Neural Networks, C.H.Dagli, A. Buczak, J. Ghosh, M. Embrechs and O.
Ersoy(eds.), Vol. 9, pp.349-354, 1999.
461.Richard Burne, Anna Buczak, Yaochu Jin, Vikram
Jamalabad, Ivan Kadar and Eitan Eadan. A self-organizing, cooperative sensor
network for remote surveillance: Current results. SPIE Proceedings, Unattended Ground Sensor Technologies and
Applications., Edward Carapezza, David Law and Terry Stalker(eds.),
Vol.3713, pp.238-248, 1999.
462.Yaochu Jin and Jingping Jiang. Techniques in neural network
based fuzzy system identification and their applications to control of complex
systems. In: Cornelius T. Leondes(ed.), Fuzzy
Theory Systems: Techniques and Applications, Chapter 5, pp.112-128, Vol. 1, Academic Press, San
Diego, USA, 1999.
463.Yaochu Jin. Decentralized adaptive fuzzy control of robot
manipulators. IEEE Transactions on Systems, Man
and Cybernetics, Part
B: Cybernetics, 28(1), 47-57, 1998
Citations
according to Google
Scholar
464.Yaochu Jin, Werner von Seelen and Bernhard Sendhoff. An approach to rule-based knowledge
extraction. In: Proceedings IEEE International
Conference on Fuzzy Systems, Anchorage, Alaska, pp.1188-1193, 1998.
Citations
according to Google
Scholar
465.Yaochu Jin and Wang Jie. Intelligent Control: Theory and
Applications,
Henan Science and Technology Publishing House, Zhengzhou, China, 1997 (in
Chinese) (ISBN: 7-5349-1983-5)
(This book is based mainly on the textbook I
prepared for a graduate course "Intelligent Control" at the
Department of Electrical Engineering, Zhejiang University during 1993-1994)
466.Yaochu Jin, Jingping Jiang. Performance analysis of fuzzy controllers based on
genetic algorithms. Pattern Recognition and Artificial
Intelligence
10(1):75-80, 1997 (in Chinese)
467.Yaochu Jin, Jingping Jiang. Two approaches to fuzzy optimal control. Proceedings of Chinese Society of Electrical Engineering. 16(3):201-204, 1996 (in Chinese)
468.Yaochu Jin and Jingping Jiang. Optimization of fuzzy control rules by means of
genetic algorithms. Control and Decision, 11(6):672-676, 1996 (in Chinese)
469.Yaochu Jin. Intelligent modeling and control of complex systems. Ph.D. thesis.
Electrical Eng. Dept., Zhejiang University, Hangzhou, May 1996
470.Yaochu Jin, Jingping Jiang and Jing Zhu. Neural network based
fuzzy identification and its applications to modeling and control of complex
systems. IEEE Transactions on Systems, Man
and Cybernetics,
25(6), 990-997, 1995
Citations
according to Google
Scholar
471.Yaochu Jin, Jing Zhu and Jingping Jiang. Adaptive fuzzy identification with
applications. International Journal of Systems
Science,6(2), 197-212, 1995.
472.Yaochu Jin, Jing Zhu. Neural network based fuzzy modeling and its simulation
techniques. Journal of Systems Simulation, 7(2):46-55, 1995 (in Chinese)
473.Yaochu Jin, Jingping Jiang. Neuro-fuzzy control of robot manipulators. Chinese Journal of Robot. 17(3):157-163, 1995 (in Chinese)
474.Yaochu Jin, Jingping Jiang. A neural network model with applications. Journal of Zhejiang University, 29(3):340-347, 1995 (in Chinese)
475.Yaochu Jin. Design and analysis of fuzzy controllers. In: J. Zhu (Ed.), Fuzzy Control, Chapter
5, pp.240-312, Mechanics Industry Press, Beijing, China, 1995 (in Chinese)
476.Yaochu Jin, Jingping Jiang. Fuzzy logic integrated multivariable adaptive
neuro-control. Information and Control, 23(4):223-228, 1994 (in Chinese)
477.Yaochu Jin, Jing Zhu. Neural network based self-learning fuzzy control. Chinese Journal of Eletronics Technology, 4:35-40, 1994 (in Chinese)
478.Yaochu Jin, Jing Zhu and Jingping Jiang. State estimation and adaptive control of
multivariable systems using fuzzy logic and neural networks. AMSE Advances in Modeling and Analysis, 43(2), 1994.
479.Yaochu Jin, Xiaodong Shen. Two-level hierarchical intelligent fuzzy control of
servo systems. Journal of Zhejiang University, 28(6):644-654, 1994 (in Chinese)
480.Yaochu Jin, Jing Zhu and Jingping Jiang. Fuzzy linearization of nonlinear systems.
In: Proceedings IEEE International Conference on Fuzzy
Systems, pp.1688-1672, Orlando, Florida,
USA, 1994
481.Yaochu Jin and Jingping Jiang. A novel paradigm of nonlinear system control with
applications. In :Proceedings IFAC Symposium on Robot
Control, Capri, Italy, 1994
482.Yaochu Jin, Jingping Jiang. Fuzzy identification with neural networks. In: Proceedings of the Chinese National Conference on Decision and Control. Xiamen, May, 1994 (in Chinese)
483.Yaochu Jin, Jingping Jiang. Adaptive fuzzy prediction with application to weather
forecast. Pattern Recognition and Artificial
Intelligence,
6(4):283-290, 1993 (in Chinese)
484.Yaochu Jin, Jingping Jiang. Neural network based non-linear feedback control. Journal of Zhejiang University, 27, 1993 (in Chinese)
485.Yaochu Jin and Jingping Jiang. Implemening self-organizing fuzzy controllers with
hybrid Pi-Sigma neural networks. In: The
Third International Workshop on Advanced Motion Control, Berkeley, California, USA, 1993
486.Yaochu Jin, Jingping Jiang. Fuzzy logic intergrated variable structure control of
a class of nonlinear systems. Control
and Decision,
7(1):36-40, 1992 (in Chinese)
487.Yaochu Jin, Jingping Jiang. Artificial neural networks in robot control- A survey.
Robot, 14(6):54-58, 1992 (in Chinese)
488.Yaochu Jin, Jingping Jiang. Neural network as fuzzy membership functions in neural
fuzzy systems. In: Proceedings of the Chinese National
Youth Conference on Robotics and Automation. Harbin, August, 1992 (in Chinese)
489.Yaochu Jin, Jingping Jiang. A novel robust adaptive control of robot manipulators.
In: Proceedings of the Chinese National Conference on
Robotics and Automation,
Harbin, Oct., 1990 (in Chinese)
490.Yaochu Jin Dynamic control of robot manipulators. Master thesis. Electrical Eng.
Dept., Zhejiang University, Hangzhou, December 1990
Last update in June, 2021.
Please pay attention to the copyrights. For enquiries, contact Yaochu Jin.