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 02/2020: Google
Scholar: h-index: 67, i10-index: 232, citations:
20,044.
Publon, h-index:
45, citations: 8,736.
Scopus
Author Profile: h-index=51, citations = 10,911;
Research
Gate: RG Score: 45.30, h-index: 60, citations: 15,109.
DBLP Computer Science Bibliography.
Ranked 57 in the UK and 966 world-wide in Computer Scientist National and World Ranking according to Guide2Research.
In Presss 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1990
1. 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, 2020 (accepted)
2. 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, 2020 (accepted)
3. Yuanjun Huang, Yaochu Jin, Kuangrong Hao. Decision-making and multi-objectivization for cost sensitive robust optimization over time. Knowledge-Based Systems, 2020 (accepted)
4. Ataollah Ramezan Shirazi and Yaochu Jin. Regulated morphogen gradients for target surrounding and adaptive shape formation. IEEE Transactions on Cognitive and Developmental Systems, 2020 (accepted)
5. Ye Tian, Chang Lu, Xingyi Zhang, and Yaochu Jin. Unsupervised neural networks for learning the sparsity of large-scale multi-objective optimization problems. IEEE Transactions on Cybernetics, 2020 (accepted)
6. 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, 2020
7.
Sampo Kuutti,
8. Yuanchao Liu, Jianchang Liu, Yaochu Jin, Fei Li, Tianzi Zheng. An affinity propagation clustering based particle swarm optimizer for dynamic optimization. Knowledge-Based Systems, 2020 (accepted)
9.
Cheng He, Ye Tian, Handing Wang, and Yaochu Jin. A
repository of real-world datasets for data-driven evolutionary multiobjective
optimization. Complex &
Intelligent Systems, 2019 (accepted)
10.
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. 2019 (accepted)
11.
Shuai Wang, Jing Liu and Yaochu
Jin. Surrogate-assisted
robust optimization of large-scale networks based on graph embedding. IEEE Transactions on Evolutionary
Computation, 2019 (accepted)
12.
Shuai Wang, Jing Liu, and Yaochu
Jin. Robust structural balance in signed networks using a multiobjective
evolutionary algorithm. IEEE
Computational Intelligence Magazine, 2019 (accepted)
13.
Hangyu Zhu and Yaochu Jin.
Multi-objective
evolutionary federated learning. IEEE
Transactions on Neural Networks and Learning Systems, 2019 (accepted)
14.
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, 2019 (accepted)
15.
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, 2019 (accepted)
16.
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, 2019 (accepted)
17.
Shuai Wang, Jing Liu and Yaochu
Jin. Finding
influential nodes in multiplex networks using a memetic algorithm. IEEE Transactions on Cybernetics, 2019
(accepted)
18.
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,
2019 (accepted)
19.
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, 2019 (accepted)
Java code here
20.
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, 2018 (accepted)
21.
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, 2018 (accepted)
22.
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, 2018
(accepted)
23.
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
24.
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
25.
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
26.
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
27.
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
28.
Lei Zhang, Hebin Pan, Xingyi Zhang, Xiangxiang Zeng and 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
29.
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, 2020
30.
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
31.
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
32. 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), Cancun, Mexico, July 2020
33. 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
34. 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
35. 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
36.
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
37.
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
38.
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
39.
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
40.
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
41.
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.
42.
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
43.
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
44.
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
45.
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
46.
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
47.
Xinjie Wang, Yaochu Jin,
and Kuangrong Hao. Echo
state networks regulated by local intrinsic plasticity rules for regression.
Neurocomputing, 351: 111-122, 2019
48.
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
49.
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
50.
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
51.
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
52.
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.
53.
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
54.
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
55.
Murillo. G. Carneiro, Ran Cheng, Liang Zhao, Yaochu Jin. Particle
swarm optimization for network-based data classification. Neural Networks, 110: 243-255, 2019
56.
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
57.
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
58.
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
59.
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
60.
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
61.
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
62.
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
63.
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
64.
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
65.
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
66.
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
67.
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
68.
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
69.
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
70.
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
71.
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
72.
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
73.
Ran Cheng, Cheng
He, Yaochu Jin, and Xin Yao. Model-based
evolutionary algorithms – A short survey. Complex & Intelligent Systems, 4:283-292, 2018
74.
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
75.
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
76.
Haibo Yu, Ying
Tan, Jianchao Zeng, Chaoli Sun and Yaochu
Jin. Surrogate-assisted
hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018
77.
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
78.
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
79.
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
80.
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.
81.
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
82.
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
83.
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
84.
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
85.
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
A draft here
Matlab code for testing LMEA on
LSMOP test suite.
MATLAB code for tree-based ENS (T-ENS)
86.
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.
87.
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
88.
Shenkai
Gu, Ran Cheng, Yaochu Jin. Feature selection for high dimensional classification using a
competitive swarm optimizer. Soft Computing,
22(3): 811-822, 2018
89.
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.
90.
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
91.
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
92.
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
93.
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
94.
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
95.
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
96.
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
97.
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
98.
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
99.
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
100.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
101.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
102.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
103.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
104.Tian
Jie, Tan Ying, Sun Chaoli, Zeng Jianchao, Yu Haibo 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
105.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
106.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
107.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
108.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
109.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
A draft here.
(This paper won the
"2017 CEC Best Student Paper Award".)
110.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.
111.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
112.Shenkai
Gu and Yaochu Jin. Multi-train:
A semi-supervised heterogeneous ensemble classifier. Neurocomputing,
249:202-211, 2017
113.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
114.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
115.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
116.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.
117.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
118.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
119.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,
14(1/2):5-25, 2017
120.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
121.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
122.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.
123.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
124.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
125.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.
126.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
127.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.
128.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
129.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
130.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
131.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
132.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
133.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
134.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
135.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
136.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.
137.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
138.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
139.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
140.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
141.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
142.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
143.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.
144.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.
145.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.
146.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.
147.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
148.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
149.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.
150.Shenkai
Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining
and Knowledge Discovery, 5(5): 234-245, 2015
151.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
See also here, Matlab code ENS_SS, ENS_BS and the NSGA-II with ENS.
(This paper won the
2017 "IEEE Transactions on Evolutionary Computation Outstanding Paper
Award".)
152.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
153.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.
154.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.
155.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
156.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
157.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
158.Yanling
Jin, Yongsheng Ding, Kuangrong Hao and Yaochu Jin.
159.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.
160.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
161.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.
162.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
(This paper won the
"2016 IEEE Computational Intelligence Outstanding Paper Award".)
163.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
164.Joseph
Chrol-Cannon and Yaochu Jin. Computational modeling of neural plasticity for self-organization
of neural networks. BioSystems, 125:43-54, 2014
Also here
165.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
166.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
167.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
168.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
169.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
170.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
171.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.
172.Spencer
A. Thomas and Yaochu Jin. Reconstructing
gene regulatory networks: Where optimization meets big data. Evolutionary
Intelligence, 7(1):29-47, 2014
173.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.
174.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
175.Ran
Cheng and Yaochu Jin. Demonstrator selection in a
social learning particle swarm optimizer. IEEE Congress on
Evolutionary Computation, July 2014, Beijing, China
176.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
177.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
178.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 ( This paper won the "Runner-up for the 2014
CEC Best Student Paper Award".) here
179.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
180.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
181.Ran
Cheng and Yaochu Jin. On the competition mechanism of the competitive
particle swarm optimizer. UK Workshop on Computational Intelligence,
September 9-11, 2013
182.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
183.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
184.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)
185.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.
186.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.
187.Mingh
Nhgia Le, Yew Soon Ong, Stefan Menzel, Yaochu Jin, and Bernhard
Sendhoff. Evolution
by adapting surrogates. Evolutionary Computation,
21(2):313-340, 2013
188.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
189.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
190.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
191.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
192.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
193.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
194.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
195.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
196.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.
197.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
198.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
199.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
200.Daniel
Bush and Yaochu Jin. Calcium control
of hippocampal STDP. Journal of Computational Neuroscience.
33(3):495-514, 2012
201.Shenkai
Gu and Yaochu Jin. Heterogeneous classifier ensembles for EEG-based
motor imaginary detection. 2012 UK Workshop on Computational Intelligence.
Edinburgh, September 2012
202.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.
203.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
204.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
205.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
206.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
207.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
208.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
209.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 (This paper won the 2014 "IEEE Computational
Intelligence Magazine Outstanding Paper Award".)
210.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.
211.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
212.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
213.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
214.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
215.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.
216.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
217.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
218.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
219.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.
220.Yan
Meng and Yaochu Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems.
Springer, 2011
221.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
222.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
223.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)
224.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.
225.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.
226.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.
227.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
228.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
229.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
230.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
231.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
232.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
233.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
234.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
235.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
236.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
237.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
238.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
239.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
240.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
241.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
242.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
243.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)
244.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.
245.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
( Best Paper Award )
246.Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS ONE,
4(12): e8177. doi:10.1371/journal.pone.0008177, 2009
247.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)
248.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)
249.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)
250.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
251.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
252.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
253.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
254.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
255.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
256.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
257.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 (Invited feature article)
Also available here
258.Yaochu
Jin and Lipo Wang (editors), Fuzzy
Systems in Bioinformatics and Computational Biology.
Springer, 2009
259.Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing
population and individual level of adaptation in changing environments. Adaptive Behavior,
17(2):153--174, 2009
260.Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto
analysis of evolutionary and learning systems. Frontiers of
Computer Science in China, 3(1):4-17, 2009
261.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
262.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
263.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
264.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
265.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
266.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
267.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
268.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
269.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
270.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.
271.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 )
272.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
273.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
274.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 ( Best
paper nomination)
275.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
276.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
277.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
278.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
279.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
280.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
281.Shengxiang
Yang, Yew-Soon Ong, and Yaochu Jin (editors) Evolutionary
Computation in Dynamic and Uncertain Environments ,
Springer, 2007
282.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
283.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
284.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.
285.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
286.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
287.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
288.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)
289.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
290.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
291.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
292.Yaochu
Jin (editor). Multi-Objective
Machine Learning. Springer, Berlin Heidelberg. 2006
293.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
294.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.
295.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
296.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
297.Dudy
Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff. Trusted
evolutionary algorithms. IEEE Congress on Evolutionary
Computation, pp.456-463, July 2006,
Vancouver
298.Lars
Gräning, Yaochu Jin, Bernhard Sendhoff. Generalization
improvement in multi-objective learning. International
Joint Conference on Neural Networks, pp.9893-9900,
July 2006, Vancouver
299.Yaochu
Jin, Bernhard Sendhoff. Alleviating catastrophic forgetting via multi-objective
learning. International Joint Conference on Neural Networks,
pp.6367-6374, July 2006, Vancouver
300.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
301.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
302.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
303.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
304.Yaochu
Jin (editor). Knowledge Incorporation in Evolutionary Computation.
Springer, Berlin Heidelberg, 2005 Table of
Contents(PDF file)
305.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
306.Hanli Wang, Sam Kwong, Yaochu Jin, Wei Wei and K.
Man. Agent-based evolutionary approach to
interpretable rule-based knowledge extraction. IEEE Transactions
Systems, Man, and Cybernetics, Part C: Applications and Reviews,
35(2), 143-155, 2005
307.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
308.Yaochu
Jin. A
comprehensive survey of fitness approximation in evolutionary computation. Soft Computing,
9(1), 3-12, 2005, Springer
Citations according to Google
Scholar
309.Michael
Huesken, Yaochu Jin and Bernhard Sendhoff.
Structure optimization of neural networks for evolutionary design optimization.
Soft
Computing, 9(1), 21-28, 2005
310.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
311.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
312.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
313.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
314.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
315.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
316.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
317.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
318.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
319.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)
320.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
321.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
322.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
323.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
324.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
325.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
326.Yaochu
Jin. Advanced Fuzzy Systems Design and Applications .
Physica-Verlag/Springer-Verlag,
Heidelberg, 2003 (ISBN: 3-7908-1537-3)Table of Contents (PDF
file).
327.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
328.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
329.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
330.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
331.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
332.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
333.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
334.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
335.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)
336.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
337.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.
338.Yaochu
Jin. Brain controlled devices -
An overview. Internal Report, Honda Research Institute Europe, HRI-EU 03-13,
September, 2003
339.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
340.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
341.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)
342.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
343.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.
344.Dissertation:
Knowledge in evolutionary and learning systems. Institute for
Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002.
(ISBN: 3-8265-9749-4)
345.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
346.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)
347.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
348.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
349.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
350.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.
351.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
352.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
353.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.
354.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.
355.Yaochu
Jin and Bernhard Sendhoff. Knowledge incorporation into neural networks from fuzzy
rules. Neural Processing Letters,
10(3), 231-242, 1999.
356.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
357.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
358.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.
359.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.
360.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.
361.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
362.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
363.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)
364.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)
365.Yaochu
Jin, Jingping Jiang. Two
approaches to fuzzy optimal control. Proceedings of Chinese
Society of Electrical Engineering. 16(3):201-204,
1996 (in Chinese)
366.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)
367.Yaochu
Jin. Intelligent modeling and
control of complex systems. Ph.D. thesis. Electrical Eng. Dept., Zhejiang
University, Hangzhou, May 1996
368.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
369.Yaochu
Jin, Jing Zhu and Jingping
Jiang. Adaptive fuzzy identification with applications. International
Journal of Systems Science,6(2), 197-212,
1995.
370.Yaochu
Jin, Jing Zhu. Neural network
based fuzzy modeling and its simulation techniques. Journal of Systems
Simulation, 7(2):46-55, 1995 (in
Chinese)
371.Yaochu
Jin, Jingping Jiang. Neuro-fuzzy
control of robot manipulators. Chinese Journal of Robot.
17(3):157-163, 1995 (in Chinese)
372.Yaochu
Jin, Jingping Jiang. A neural
network model with applications. Journal of Zhejiang
University, 29(3):340-347, 1995 (in
Chinese)
373.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)
374.Yaochu
Jin, Jingping Jiang. Fuzzy logic
integrated multivariable adaptive neuro-control. Information and
Control, 23(4):223-228, 1994 (in Chinese)
375.Yaochu
Jin, Jing Zhu. Neural network
based self-learning fuzzy control. Chinese Journal of Eletronics
Technology, 4:35-40, 1994 (in Chinese)
376.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.
377.Yaochu
Jin, Xiaodong Shen. Two-level
hierarchical intelligent fuzzy control of servo systems. Journal of
Zhejiang University, 28(6):644-654, 1994 (in
Chinese)
378.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
379.Yaochu
Jin and Jingping Jiang. A novel
paradigm of nonlinear system control with applications. In :Proceedings IFAC
Symposium on Robot Control, Capri, Italy,
1994
380.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)
381.Yaochu
Jin, Jingping Jiang. Adaptive
fuzzy prediction with application to weather forecast. Pattern
Recognition and Artificial Intelligence, 6(4):283-290, 1993
(in Chinese)
382.Yaochu
Jin, Jingping Jiang. Neural
network based non-linear feedback control. Journal of Zhejiang
University, 27, 1993 (in Chinese)
383.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
384.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)
385.Yaochu
Jin, Jingping Jiang. Artificial
neural networks in robot control- A survey. Robot,
14(6):54-58, 1992 (in Chinese)
386.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)
387.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)
388.Yaochu
Jin Dynamic control of robot
manipulators. Master thesis. Electrical Eng. Dept., Zhejiang University,
Hangzhou, December 1990
Last update in January, 2019. Please pay attention to
the copyrights. For enquiries, contact Yaochu Jin.