Chaotic Hopfield Neural Network Swarm Optimization and Its Application
A new neural network based optimization algorithm is proposed. The presented model is a discrete-time, continuous-state Hopfield neural network and the states of the model are updated synchronously. The proposed algorithm combines the advantages of traditional PSO, chaos and Hopfield neural networks...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/873670 |
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| _version_ | 1832561858710601728 |
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| author | Yanxia Sun Zenghui Wang Barend Jacobus van Wyk |
| author_facet | Yanxia Sun Zenghui Wang Barend Jacobus van Wyk |
| author_sort | Yanxia Sun |
| collection | DOAJ |
| description | A new neural network based optimization algorithm is proposed. The presented model is a discrete-time, continuous-state Hopfield neural network and the states of the model are updated synchronously. The proposed algorithm combines the advantages of traditional PSO, chaos and Hopfield neural networks: particles learn from their own experience and the experiences of surrounding particles, their search behavior is ergodic, and convergence of the swarm is guaranteed. The effectiveness of the proposed approach is demonstrated using simulations and typical optimization problems. |
| format | Article |
| id | doaj-art-9262510e92b2418bafc85495b5b6ebd5 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-9262510e92b2418bafc85495b5b6ebd52025-02-03T01:24:06ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/873670873670Chaotic Hopfield Neural Network Swarm Optimization and Its ApplicationYanxia Sun0Zenghui Wang1Barend Jacobus van Wyk2Department of Electrical Engineering, Tshwane University of Technology, Pretoria 0001, South AfricaSchool of Engineering, University of South Africa, Florida 1710, South AfricaDepartment of Electrical Engineering, Tshwane University of Technology, Pretoria 0001, South AfricaA new neural network based optimization algorithm is proposed. The presented model is a discrete-time, continuous-state Hopfield neural network and the states of the model are updated synchronously. The proposed algorithm combines the advantages of traditional PSO, chaos and Hopfield neural networks: particles learn from their own experience and the experiences of surrounding particles, their search behavior is ergodic, and convergence of the swarm is guaranteed. The effectiveness of the proposed approach is demonstrated using simulations and typical optimization problems.http://dx.doi.org/10.1155/2013/873670 |
| spellingShingle | Yanxia Sun Zenghui Wang Barend Jacobus van Wyk Chaotic Hopfield Neural Network Swarm Optimization and Its Application Journal of Applied Mathematics |
| title | Chaotic Hopfield Neural Network Swarm Optimization and Its Application |
| title_full | Chaotic Hopfield Neural Network Swarm Optimization and Its Application |
| title_fullStr | Chaotic Hopfield Neural Network Swarm Optimization and Its Application |
| title_full_unstemmed | Chaotic Hopfield Neural Network Swarm Optimization and Its Application |
| title_short | Chaotic Hopfield Neural Network Swarm Optimization and Its Application |
| title_sort | chaotic hopfield neural network swarm optimization and its application |
| url | http://dx.doi.org/10.1155/2013/873670 |
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