Download e-book for kindle: Advances in Neural Networks – ISNN 2009: 6th International by Minghui Jiang, Yongqing Zhao, Yi Shen (auth.), Wen Yu, Haibo

By Minghui Jiang, Yongqing Zhao, Yi Shen (auth.), Wen Yu, Haibo He, Nian Zhang (eds.)

ISBN-10: 3642015123

ISBN-13: 9783642015120

ISBN-10: 3642015131

ISBN-13: 9783642015137

The 3 quantity set LNCS 5551/5552/5553 constitutes the refereed court cases of the sixth foreign Symposium on Neural Networks, ISNN 2009, held in Wuhan, China in may possibly 2009.

The 409 revised papers offered have been rigorously reviewed and chosen from a complete of 1.235 submissions. The papers are prepared in 20 topical sections on theoretical research, balance, time-delay neural networks, computing device studying, neural modeling, determination making structures, fuzzy platforms and fuzzy neural networks, aid vector machines and kernel equipment, genetic algorithms, clustering and type, development acceptance, clever keep an eye on, optimization, robotics, snapshot processing, sign processing, biomedical purposes, fault prognosis, telecommunication, sensor community and transportation platforms, in addition to applications.

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Extra resources for Advances in Neural Networks – ISNN 2009: 6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings, Part III

Sample text

Hybrid Recursive Particle Swarm Optimization Learning Algorithm in the Design of Radial Basis Function Networks. Journal of Marine Science and Technology 15, 31–40 (2007) 14. : Multivariable Functional Interpolation and Adaptive Networks. cn Abstract. A new version of the classical particle swarm optimization (PSO), namely, Chaos culture particle swam optimization (CCPSO), is proposed to overcome the shortcoming of the premature of the classical PSO. The proposed algorithm integrates PSO with the framework of cultural algorithm model.

ISNN 2009, Part III, LNCS 5553, pp. 19–29, 2009. N. M. Shamsuddin Networks. The number of basis functions controls the complexity and the generalization ability of RBF Networks. RBF Networks with too few basis functions cannot fit the training data adequately due to limited flexibility. On the other hand, those with too many basis functions yield poor generalization abilities since they are too flexible and fit the noise in the training data. The methods mentioned above require designers to fix the structure of networks in advance according to prior knowledge.

Cn Abstract. A new version of the classical particle swarm optimization (PSO), namely, Chaos culture particle swam optimization (CCPSO), is proposed to overcome the shortcoming of the premature of the classical PSO. The proposed algorithm integrates PSO with the framework of cultural algorithm model. PSO is utilized as the evolution method of population space. Meanwhile, the chaotic search operator is imported to build the knowledge structure of belief space, with which guiding the evolution process of the proposed algorithm, moving particles to the global optimal solution can be more effective.

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Advances in Neural Networks – ISNN 2009: 6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings, Part III by Minghui Jiang, Yongqing Zhao, Yi Shen (auth.), Wen Yu, Haibo He, Nian Zhang (eds.)


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