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Training method for a feed forward neural network based on meta-heuristics

This paper proposes a Gaussian-Cauchy Particle Swarm Optimization (PSO) algorithm to provide the optimized parameters for a Feed Forward Neural Network. The improved PSO trains the Neural Network by optimizing the network weights and bias in the Neural Network. In comparison with the Back Propagatio...

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Main Authors: Melo, H., Zhang, H., Vasant, P., Watada, J.
Format: Article
Published: Springer Science and Business Media Deutschland GmbH 2018
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026662697&doi=10.1007%2f978-3-319-63859-1_46&partnerID=40&md5=4ced0da20f5776abff3e471bacd835ca
http://eprints.utp.edu.my/21979/
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spelling my.utp.eprints.219792019-02-20T01:52:16Z Training method for a feed forward neural network based on meta-heuristics Melo, H. Zhang, H. Vasant, P. Watada, J. This paper proposes a Gaussian-Cauchy Particle Swarm Optimization (PSO) algorithm to provide the optimized parameters for a Feed Forward Neural Network. The improved PSO trains the Neural Network by optimizing the network weights and bias in the Neural Network. In comparison with the Back Propagation Neural Network, the Gaussian-Cauchy PSO Neural Network converges faster and is immune to local minima. © Springer International Publishing AG 2018. Springer Science and Business Media Deutschland GmbH 2018 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026662697&doi=10.1007%2f978-3-319-63859-1_46&partnerID=40&md5=4ced0da20f5776abff3e471bacd835ca Melo, H. and Zhang, H. and Vasant, P. and Watada, J. (2018) Training method for a feed forward neural network based on meta-heuristics. Smart Innovation, Systems and Technologies, 82 . pp. 378-385. http://eprints.utp.edu.my/21979/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description This paper proposes a Gaussian-Cauchy Particle Swarm Optimization (PSO) algorithm to provide the optimized parameters for a Feed Forward Neural Network. The improved PSO trains the Neural Network by optimizing the network weights and bias in the Neural Network. In comparison with the Back Propagation Neural Network, the Gaussian-Cauchy PSO Neural Network converges faster and is immune to local minima. © Springer International Publishing AG 2018.
format Article
author Melo, H.
Zhang, H.
Vasant, P.
Watada, J.
spellingShingle Melo, H.
Zhang, H.
Vasant, P.
Watada, J.
Training method for a feed forward neural network based on meta-heuristics
author_facet Melo, H.
Zhang, H.
Vasant, P.
Watada, J.
author_sort Melo, H.
title Training method for a feed forward neural network based on meta-heuristics
title_short Training method for a feed forward neural network based on meta-heuristics
title_full Training method for a feed forward neural network based on meta-heuristics
title_fullStr Training method for a feed forward neural network based on meta-heuristics
title_full_unstemmed Training method for a feed forward neural network based on meta-heuristics
title_sort training method for a feed forward neural network based on meta-heuristics
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2018
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026662697&doi=10.1007%2f978-3-319-63859-1_46&partnerID=40&md5=4ced0da20f5776abff3e471bacd835ca
http://eprints.utp.edu.my/21979/
_version_ 1738656365058981888
score 13.211869

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