Input selection using binary particle swarm optimization

Amonchanchaigul, Thavit; Kreesuradej, Worapoj

doi:10.1109/CIMCA.2006.127

Input selection using binary particle swarm optimization

Author(s)

Amonchanchaigul, Thavit

Kreesuradej, Worapoj

Date Issued

January 1, 2006

Type

Conference Paper

DOI

10.1109/CIMCA.2006.127

Abstract

Nowadays, multi-layer feed forward networks are often used for modeling complex relationships between the data sets. And if we can choose only the important data from the training sets, it will make the networks less size and can save more time. Because we realize in this point, this paper provides procedure of feature selection to train the neural networks using binary particle swarm optimization. It also introduces the suitable function for the binary particle swarm optimization technique by changing concept in part of member value adjustment function for each particle. © 2006 IEEE.

Citation

Cimca 2006 International Conference on Computational Intelligence for Modelling Control and Automation Jointly with Iawtic 2006 International Conference on Intelligent Agents Web Technologies, 159, 2006