Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems
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...
Main Authors: | Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Utara Malaysia Press
2012
|
Subjects: | |
Online Access: | https://repo.uum.edu.my/id/eprint/30417/1/JICT%2011%2000%202012%2037-53.pdf |
Similar Items
-
Artificial fish swarm optimization for multilayer network learning in classification problems
by: Hasan, Shafaatunnur, et al.
Published: (2012) -
Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
by: Hasan, Shafaatunnur, et al.
Published: (2011) -
OctaSOM - An octagonal based SOM lattice structure for biomedical problems
by: Hasan, Shafaatunnur, et al.
Published: (2015) -
Swarm negative selection algorithm for electroencephalogram signals classification
by: Sahel Ba-Karait, Nasser Omer, et al.
Published: (2009) -
Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model
by: Salleh, Roselina, et al.
Published: (2007)