Improving robustness of artificial neural networks model using genetic algorithm
Artificial Neural Networks (ANN) has been widely accepted as process estimators due its ability to capture complex relationships. However, experiences in implementing ANN estimators in research and industry have exposed some weakness that can be detrimental to the overall performance of plant operat...
Main Authors: | Ahmad, Arshad, Chen, Wah Sit |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Malaysia Sabah
2003
|
Subjects: | |
Online Access: | http://eprints.utm.my/8025/1/ArshadAhmad2003_ImprovingRobustnessOfArtificialNeuralNetworks.pdf |
Similar Items
-
Application of artificial neural network genetic algorithm in inferential estimation and control of a distillation column
by: Chen, Wah Sit
Published: (2005) -
Model-based fault detection using hierarchical artificial neural network
by: Ahmad, Arshad, et al.
Published: (2001) -
Development of a robust hybrid estimator using partial least squares regression and artificial neural networks.
by: Ahmad, Arshad, et al.
Published: (2003) -
Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production
by: Abdul Sahli, Fakharudin, et al.
Published: (2013) -
Process identification using artificial neural network
by: Ahmad, Arshad
Published: (1995)