A Constrained Multi-Objective Learning Algorithm for Feed-Forward Neural Network Classifiers

A Constrained Multi-Objective Learning Algorithm for Feed-Forward Neural Network Classifiers

Show other versions (1)

This paper proposes a new approach to address the optimal design of a Feed-forward Neural Network (FNN) based classifier. The originality of the proposed methodology, called CMOA, lie in the use of a new constraint handling technique based on a self-adaptive penalty procedure in order to direct the...

Full description

Bibliographic Details
Main Authors: M. Njah, R. El Hamdi
Format: Article
Language:English
Published: D. G. Pylarinos 2017-06-01
Series:Engineering, Technology & Applied Science Research
Subjects:
FNN Classifier
Constrained Multi-Objective Optimization
Pareto Dominance Criterion
Differential Evolution
Online Access:http://etasr.com/index.php/ETASR/article/view/968/503

Internet

http://etasr.com/index.php/ETASR/article/view/968/503

Similar Items