In Presss    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   

In Press / Accepted / Under Review

1. Handing Wang, Yaochu Jin, and John Doherty. Committee-based active learning for surrogate-assisted particle swarm optimization of expensive problems. IEEE Transactions on Cybernetics, 2017 (accepted)


2. 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, 2017 (accepted)


3. 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, 2017 (accepted)


4. 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, 2016 (accepted)


5. 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, 2016 (accepted)


6. 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, 2016 (accepted)


7. 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, 2016 (accepted). A draft here.


8. Shenkai Gu, Ran Cheng, Yaochu Jin. Feature selection for high dimensional classification using a competitive swarm optimizer. Soft Computing, 2016. DOI: 10.1007/s00500-016-2385-6 (accepted)


9. 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, 2016 (accepted)
   A draft here
   Matlab code for testing LMEA on LSMOP test suite.
   MATLAB code for tree-based ENS (T-ENS)


10. Ran Cheng, Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. Test problems for large-scale multiobjective and many-objective optimization. IEEE Transactions on Cybernetics. (Accepted).
    A draft here
    Source code for the proposed test problems.
    Supplimentary materials


11. Chaoli Sun, Jinliang Ding, Jianchao Zeng and Yaochu Jin. Fitness approximation assisted competitive swarm optimizer for large scale expensive optimization problems. Memetic Computing, 2016 (accepted).


12. Hyondong Oh, Ataollah R. Shiraz, Yaochu Jin. Morphogen diffusion algorithms for tracking and herding using a swarm of Kilobots. Soft Computing, 2016 (accepted)


13. Du-Juan Wang, Feng Liu and Yaochu Jin. A proactive scheduling approach to steel rolling process with stochastic machine breakdown. Natural Computing. 2016 (accepted)


14. Xin Ye, Jia Li, Sihao Liu, Jiwei Liang and Yaochu Jin. A hybrid instance-intensive workflow scheduling method in private cloud environment. Natural Computing. 2016 (accepted)


15. Guangshun Yao,Yongsheng Ding, Yaochu Jin, Kuangrong Hao. Endocrine-based coevolutionary multi-swarm for multi-objective workflow scheduling in a cloud system. Soft Computing, 2015 (accepted) [return to top]

    2017

16. 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, June 2017
    A draft here.
    (This paper won the "2017 CEC Best Student Paper Award".)


17. 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.


18. Shenkai Gu and Yaochu Jin. Multi-train: A semi-supervised heterogeneous ensemble classifier. Neurocomputing, 249:202-211, 2017


19. 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


20. 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


21. 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


22. 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.


23. 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


24. 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


25. 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


26. Handing Wang and Yaochu Jin. Efficient nonlinear correlation detection for decomposed search in evolutionary multi-objective optimization. Congress on Evolutionary Computation, June 2017

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2016

27. 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.


28. 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


29. 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


30. 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.


31. 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
    


32. 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.


33. 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


34. 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


35. 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


36. 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


37. 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


38. 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


39. 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


40. 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


41. 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.


42. 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


43. 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


44. 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


45. 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


46. 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


47. 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

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2015

48. 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.


49. 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.


50. 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.


51. 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.


52. 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


53. 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


54. 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.


55. Shenkai Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining and Knowledge Discovery, 5(5): 234-245, 2015


56. 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".)


57. 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


58. 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.


59. 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.


60. 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


61. 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


62. 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


63. Yanling Jin, Yongsheng Ding, Kuangrong Hao and Yaochu Jin. An endocrine-based intelligent distributed cooperative algorithm for target tracking in wireless sensor networks. Soft Computing, 19(5):1427-1441, 2015


64. 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.


65. 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


66. 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.

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2014

67. 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".)


68. 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


69. Joseph Chrol-Cannon and Yaochu Jin. Computational modeling of neural plasticity for self-organization of neural networks. BioSystems, 125:43-54, 2014 Also here


70. 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


71. 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


72. 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


73. 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


74. 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


75. 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


76. 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.


77. Spencer A. Thomas and Yaochu Jin. Reconstructing gene regulatory networks: Where optimization meets big data. Evolutionary Intelligence, 7(1):29-47, 2014


78. 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


79. 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


80. Ran Cheng and Yaochu Jin. Demonstrator selection in a social learning particle swarm optimizer. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China


81. 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


82. 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


83. 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

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2013

84. 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


85. 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


86. Ran Cheng and Yaochu Jin. On the competition mechanism of the competitive particle swarm optimizer. UK Workshop on Computational Intelligence, September 9-11, 2013


87. 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


88. 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


89. 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)


90. 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.


91. 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.


92. Mingh Nhgia Le, Yew Soon Ong, Stefan Menzel, Yaochu Jin, and Bernhard Sendhoff. Evolution by adapting surrogates. Evolutionary Computation, 21(2):313-340, 2013


93. 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


94. 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


95. 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


96. 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


97. 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


98. 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


99. 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


100. 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


101. 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.


102. 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

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2012

103. 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


104. 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


105. Daniel Bush and Yaochu Jin. Calcium control of hippocampal STDP. Journal of Computational Neuroscience. 33(3):495-514, 2012


106. Shenkai Gu and Yaochu Jin. Heterogeneous classifier ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012


107. 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.


108. 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


109. 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


110. 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


111. 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


112. 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


113. 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


114. 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".)

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2011

115. 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.


116. 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


117. 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


118. 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


119. 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


120. 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.


121. 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


122. 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


123. 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


124. 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.


125. Yan Meng and Yaochu Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems. Springer, 2011


126. 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


127. 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


128. 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)


129. 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.
     


130. 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.


131. 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.


132. 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


133. 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


134. 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


135. 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

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2010

136. 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


137. 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


138. 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


139. 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


140. 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


141. 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


142. 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


143. 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


144. 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


145. 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


146. 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


147. 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


148. 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)


149. 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.


150. 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 )

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2009

151. Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177, 2009


152. 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)


153. 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)


154. 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)


155. 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


156. 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


157. 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


158. 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


159. 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


160. 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


161. 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


162. 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


163. Yaochu Jin and Lipo Wang (editors), Fuzzy Systems in Bioinformatics and Computational Biology. Springer, 2009


164. Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing population and individual level of adaptation in changing environments. Adaptive Behavior, 17(2):153--174, 2009


165. Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto analysis of evolutionary and learning systems. Frontiers of Computer Science in China, 3(1):4-17, 2009


166. 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


167. 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


168. 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


169. 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


170. 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


171. 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


172. 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


173. 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


174. 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

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2008

175. 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.


176. 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 )


177. 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


178. 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


179. 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)


180. 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


181. 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


182. 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


183. 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


184. 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


185. 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

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2007

186. Shengxiang Yang, Yew-Soon Ong, and Yaochu Jin (editors) Evolutionary Computation in Dynamic and Uncertain Environments , Springer, 2007


187. 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


188. 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


189. 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.


190. 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


191. 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


192. 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


193. 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)


194. 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


195. 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


196. 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

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2006

197. Yaochu Jin (editor). Multi-Objective Machine Learning. Springer, Berlin Heidelberg. 2006


198. 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


199. 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.


200. 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


201. 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


202. Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff. Trusted evolutionary algorithms. IEEE Congress on Evolutionary Computation, pp.456-463, July 2006, Vancouver


203. Lars Gräning, Yaochu Jin, Bernhard Sendhoff. Generalization improvement in multi-objective learning. International Joint Conference on Neural Networks, pp.9893-9900, July 2006, Vancouver


204. Yaochu Jin, Bernhard Sendhoff. Alleviating catastrophic forgetting via multi-objective learning. International Joint Conference on Neural Networks, pp.6367-6374, July 2006, Vancouver


205. 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


206. 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

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2005

207. 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


208. 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


209. Yaochu Jin (editor). Knowledge Incorporation in Evolutionary Computation. Springer, Berlin Heidelberg, 2005 Table of Contents(PDF file)


210. 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


211. 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


212. 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


213. Yaochu Jin. A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing, 9(1), 3-12, 2005, Springer
     Citations according to Google Scholar


214. Michael Huesken, Yaochu Jin and Bernhard Sendhoff. Structure optimization of neural networks for evolutionary design optimization. Soft Computing, 9(1), 21-28, 2005


215. 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


216. 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


217. 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


218. 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


219. 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


220. 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


221. 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


222. 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

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2004

223. 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


224. 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)


225. 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


226. 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


227. 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


228. 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


229. 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


230. 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

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2003

231. Yaochu Jin. Advanced Fuzzy Systems Design and Applications . Physica-Verlag/Springer-Verlag, Heidelberg, 2003 (ISBN: 3-7908-1537-3)Table of Contents (PDF file).


232. 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


233. 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


234. 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


235. 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


236. 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


237. 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


238. 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


239. 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


240. 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)


241. 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


242. 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.


243. Yaochu Jin. Brain controlled devices - An overview. Internal Report, Honda Research Institute Europe, HRI-EU 03-13, September, 2003

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2002

244. 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


245. 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


246. 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)


247. 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


248. 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.


249. Dissertation: Knowledge in evolutionary and learning systems. Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002. (ISBN: 3-8265-9749-4)


250. 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


251. 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)

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2001

252. 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


253. 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


254. 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


255. 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.


256. 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

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2000

257. 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


258. 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.


259. 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.

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1999

260. Yaochu Jin and Bernhard Sendhoff. Knowledge incorporation into neural networks from fuzzy rules. Neural Processing Letters, 10(3), 231-242, 1999.


261. 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


262. 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


263. 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.


264. 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.


265. 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.

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1998

266. 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


267. 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

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1997

268. 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)


269. 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)

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1996

270. Yaochu Jin, Jingping Jiang. Two approaches to fuzzy optimal control. Proceedings of Chinese Society of Electrical Engineering. 16(3):201-204, 1996 (in Chinese)


271. 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)


272. Yaochu Jin. Intelligent modeling and control of complex systems. Ph.D. thesis. Electrical Eng. Dept., Zhejiang University, Hangzhou, May 1996

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1995

273. 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


274. Yaochu Jin, Jing Zhu and Jingping Jiang. Adaptive fuzzy identification with applications. International Journal of Systems Science,6(2), 197-212, 1995.


275. Yaochu Jin, Jing Zhu. Neural network based fuzzy modeling and its simulation techniques. Journal of Systems Simulation, 7(2):46-55, 1995 (in Chinese)


276. Yaochu Jin, Jingping Jiang. Neuro-fuzzy control of robot manipulators. Chinese Journal of Robot. 17(3):157-163, 1995 (in Chinese)


277. Yaochu Jin, Jingping Jiang. A neural network model with applications. Journal of Zhejiang University, 29(3):340-347, 1995 (in Chinese)


278. 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)

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1994

279. Yaochu Jin, Jingping Jiang. Fuzzy logic integrated multivariable adaptive neuro-control. Information and Control, 23(4):223-228, 1994 (in Chinese)


280. Yaochu Jin, Jing Zhu. Neural network based self-learning fuzzy control. Chinese Journal of Eletronics Technology, 4:35-40, 1994 (in Chinese)


281. 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.


282. Yaochu Jin, Xiaodong Shen. Two-level hierarchical intelligent fuzzy control of servo systems. Journal of Zhejiang University, 28(6):644-654, 1994 (in Chinese)


283. 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


284. Yaochu Jin and Jingping Jiang. A novel paradigm of nonlinear system control with applications. In :Proceedings IFAC Symposium on Robot Control, Capri, Italy, 1994


285. 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)

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1993

286. Yaochu Jin, Jingping Jiang. Adaptive fuzzy prediction with application to weather forecast. Pattern Recognition and Artificial Intelligence, 6(4):283-290, 1993 (in Chinese)


287. Yaochu Jin, Jingping Jiang. Neural network based non-linear feedback control. Journal of Zhejiang University, 27, 1993 (in Chinese)


288. 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

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1992

289. 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)


290. Yaochu Jin, Jingping Jiang. Artificial neural networks in robot control- A survey. Robot, 14(6):54-58, 1992 (in Chinese)


291. 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)

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1990

292. 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)


293. Yaochu Jin Dynamic control of robot manipulators. Master thesis. Electrical Eng. Dept., Zhejiang University, Hangzhou, December 1990

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Last update in January, 2016. Please pay attention to the copyrights. For enquiries, contact Yaochu Jin.