Bio-Inspired Computing - Theories and Applications: 9th by Linqiang Pan, Gheorghe Paun, Mario J. Pérez-Jiménez, Tao

By Linqiang Pan, Gheorghe Paun, Mario J. Pérez-Jiménez, Tao Song

This publication constitutes the court cases of the ninth foreign convention on Bio-inspired Computing: Theories and functions, BIC-TA 2014, held in Wuhan, China, in October 2014. The 109 revised complete papers awarded have been conscientiously reviewed and chosen from 204 submissions. The papers specialise in 4 major subject matters, specifically evolutionary computing, neural computing, DNA computing, and membrane computing.

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Syst. Man. Cy. C. Appl. Rev. 34(4), 523–531 (2004) 2. : Fuzzy Knowledge Representation Based on An Improving Spiking Neural P System. In: Proceedings of the 6th International Conference on Natural Computation (2010) 3. : Petri Net based PLC Stage Programming for Discrete-event Control Design. In: Proceedings of the 2001 International Conference on IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 2706–2710 (2001) 4. : Visual PLC-Programming using Signal Interpreted Petri Nets.

12ZZ007), the National Natural Science Foundation of China (Grant No. 61170030), and Foundation for International Cooperation of Ministry of Science and Technology, China (No: SQ2011ZOF000004), and the Ministry of Education Chunhui Project of China (No. Z2012025). References 1. : Ladder Diagram And Petri-Net-Based Discrete-Event Control Design Methods. IEEE T. Syst. Man. Cy. C. Appl. Rev. 34(4), 523–531 (2004) 2. : Fuzzy Knowledge Representation Based on An Improving Spiking Neural P System. In: Proceedings of the 6th International Conference on Natural Computation (2010) 3.

The first one means the ability of the algorithm to “explore” or search every region of the feasible search space, while the second denotes the ability to converge to the near-optimal solutions as quickly as possible [1,2]. Practical experience, however, shows that existing RCGAs still may occasionally stop proceeding toward the global optimum even though the population has not converged to a local optimum or any other point. In fact, it is impossible there is a general tractable algorithm that could efficiently and effectively solve all possible complexities of real-life optimization problems [2], which motivates researchers to develop better algorithms that yield better approximate solutions.

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Bio-Inspired Computing - Theories and Applications: 9th by Linqiang Pan, Gheorghe Paun, Mario J. Pérez-Jiménez, Tao
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