ARTIFICIAL FISH SWARM OPTMIZATION FOR MULTILAYERNETWORK LEARNING IN CLASSIFICATION PROBLEMS

ARTIFICIAL FISH SWARM OPTMIZATION FOR MULTILAYERNETWORK LEARNING IN CLASSIFICATION PROBLEMS

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Nature-Inspired Computing (NIC) has always been a promising tool to enhance neural network learning. Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN. In this study, we applied the AFSA method to improve the Multilayer Percept...

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Bibliographic Details
Main Authors: Shafaatunnur Hasan, Tan Swee Quo, Siti Mariyam Shamsuddin, Roselina Sallehuddin
Format: Article
Language:English
Published: UUM Press 2012-04-01
Series:Journal of ICT
Subjects:
Artificial neural network
artificial fish swarm algorithm
classification problems
Online Access:https://e-journal.uum.edu.my/index.php/jict/article/view/8123

Internet

https://e-journal.uum.edu.my/index.php/jict/article/view/8123

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