By Yong Liu (auth.), Lishan Kang, Zhihua Cai, Xuesong Yan, Yong Liu (eds.)
This e-book constitutes the refereed court cases of the 3rd overseas Symposium on Intelligence Computation and functions, ISICA 2008, held in Wuhan, China, in December 2008.
The ninety three revised complete papers have been conscientiously reviewed and chosen from approximately seven-hundred submissions. The papers are prepared in topical sections on computational intelligence, evolutionary computation, evolutionary multi-objective and dynamic optimization, evolutionary studying structures, neural networks, category and popularity, bioinformatics and bioengineering, evolutionary facts mining and information discovery, clever GIS and keep an eye on, idea of clever computation, combinational and numerical optimization, in addition to real-world applications.
Read or Download Advances in Computation and Intelligence: Third International Symposium, ISICA 2008 Wuhan, China, December 19-21, 2008 Proceedings PDF
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Extra info for Advances in Computation and Intelligence: Third International Symposium, ISICA 2008 Wuhan, China, December 19-21, 2008 Proceedings
For (µ+λ) and (µ,λ) evolutionary algorithms where µ<λ, IFEP would be particularly attractive since a parent has to generate more than one offspring. It may be beneficial if different offspring are generated by different mutations . A Self-adaptive Evolutionary Programming Based on Optimum Search Direction 17 Acknowledgements This paper supported by the National Natural Science Foundation of China (No. 60473081) and Shenzhen Science and Technology Project (No. SZKJ0706). References 1. : Artificial Intelligence Through Simulated Evolution.
No prior knowledge or any complicated operators were use, and also no additional parameter was used either. g. “step sizes”) and optimum search direction in a robust search algorithm. It is that Cauchy mutations played a major role in the population in the early stages of evolution since the distance between the current search points and the global optimum was relatively large on average in the early stages, hence Cauchy mutation performed better. However, as the evolution progress, the distance became smaller and smaller.
Methods of Optimization. John Wiley and Sons, London (1975) 11. : Teoria i metody obliczeniowe optymalizacji. PWN, Warszawa (1980) 12. : An Analysis of Behavior of a Class of Genetic Adaptive Systems. D. thesis, University of Michigan, Ann Arbor, Michigan (1975) 13. : Generalized Descent for Global Optimization. JOTA 34, 11–39 (1981) 14. : Evolutionary Computation, pp. 67–68. com Abstract. Gene expression programming (GEP) is a recently developed evolutionary computation method for model learning and knowledge discovery.