Dynamic characteristic of a multiple chaotic neural network and its application
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- 作者：Gang Yang (1)
Junyan Yi (3) - 关键词：Chaotic dynamics ; Annealing strategy ; Combinatorial optimization ; Neural network
- 刊名：Soft Computing - A Fusion of Foundations, Methodologies and Applications
- 出版年：2013
- 出版时间：May 2013
- 年：2013
- 卷：17
- 期：5
- 页码：783-792
- 全文大小：666 KB
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Junyan Yi (3)
1. Key Laboratory of Data Engineering and Knowledge Engineering, Renmin University of China, MOE, Beijing, 100872, People鈥檚 Republic of China
3. Department of Computer Science and Technology, Zhejiang University of Technology, Chaowang Road 18, Hangzhou, 310026, Zhejiang Province, People鈥檚 Republic of China - ISSN：1433-7479
文摘
Based on chaotic neural network, a multiple chaotic neural network algorithm combining two different chaotic dynamics sources in each neuron is proposed. With the effect of self-feedback connection and non-linear delay connection weight, the new algorithm can contain more powerful chaotic dynamics to search the solution domain globally in the beginning searching period. By analyzing the dynamic characteristic and the influence of cooling schedule in simulated annealing, a flexible parameter tuning strategy being able to promote chaotic dynamics convergence quickly is introduced into our algorithm. We show the effectiveness of the new algorithm in two difficult combinatorial optimization problems, i.e., a traveling salesman problem and a maximum clique problem.