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...
Saved in:
| Main Authors: | , , , |
|---|---|
| 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/21329/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Petronas |
| id |
my.utp.eprints.21329 |
|---|---|
| record_format |
eprints |
| spelling |
my.utp.eprints.213292018-09-25T07:22:33Z 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 NonPeerReviewed 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/21329/ |
| 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/21329/ |
| _version_ |
1738656274017419264 |