Chaotic Hopfield Neural Network Swarm Optimization and Its Application
Joint Authors
Wang, Zenghui
van Wyk, Barend Jacobus
Sun, Yanxia
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-15
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Sun, Yanxia& Wang, Zenghui& van Wyk, Barend Jacobus. 2013. Chaotic Hopfield Neural Network Swarm Optimization and Its Application. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-505214
Modern Language Association (MLA)
Sun, Yanxia…[et al.]. Chaotic Hopfield Neural Network Swarm Optimization and Its Application. Journal of Applied Mathematics No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-505214
American Medical Association (AMA)
Sun, Yanxia& Wang, Zenghui& van Wyk, Barend Jacobus. Chaotic Hopfield Neural Network Swarm Optimization and Its Application. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-505214
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-505214