Evolutionary Computation and Its Applications in Neural and Fuzzy Systems
Joint Authors
Du, K.-L.
Lu, Jiabin
Zhang, Biaobiao
Wu, Yue
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-10-13
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Information Technology and Computer Science
Abstract EN
Neural networks and fuzzy systems are two soft-computing paradigms for system modelling.
Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization.
Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques.
Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum.
Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel.
Evolutionary algorithms are a major approach to adaptation and optimization.
In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies.
Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described.
Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made.
Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.
American Psychological Association (APA)
Zhang, Biaobiao& Wu, Yue& Lu, Jiabin& Du, K.-L.. 2011. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems. Applied Computational Intelligence and Soft Computing،Vol. 2011, no. 2011, pp.1-20.
https://search.emarefa.net/detail/BIM-509733
Modern Language Association (MLA)
Zhang, Biaobiao…[et al.]. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems. Applied Computational Intelligence and Soft Computing No. 2011 (2011), pp.1-20.
https://search.emarefa.net/detail/BIM-509733
American Medical Association (AMA)
Zhang, Biaobiao& Wu, Yue& Lu, Jiabin& Du, K.-L.. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems. Applied Computational Intelligence and Soft Computing. 2011. Vol. 2011, no. 2011, pp.1-20.
https://search.emarefa.net/detail/BIM-509733
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-509733