A Nonlinear Model Predictive Control Strategy Using Multiple Neural Network Models.
Combining multiple neural networks appears to be a very promising approach for improving neural network generalization since it is very difficult, if not impossible, to develop a perfect single neural network.
Saved in:
Main Authors: | Ahmad, Zainal, Jie, Zhang |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2006
|
Subjects: | |
Online Access: | http://eprints.usm.my/15567/1/nonlinear.pdf http://eprints.usm.my/15567/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Nonlinear process modeling of pH neutralization process in CSTR using,selective combination of multiple neural Networks.
by: Ahmad, Zainal Ariffin, et al.
Published: (2008) -
Nonlinear Model Predictive Control Of A Distillation Column Using Hammerstein Model And Nonlinear Autoregressive Model With Exogenous Input.
by: Kanthasamy, Ramesh
Published: (2009) -
Development Of Multiple-Input Multiple-Output (MIMO) And Multiple-Input Single-Out (MISO) Neural Network Models For Continuos Distillation Column.
by: Abdullah, Zalizawati
Published: (2008) -
Nonlinear Autoregressive With Exogenous Input Model Based Control Strategy For Batch Esterification Reactor
by: Zulkeflee, Asyura Binti
Published: (2009) -
Modeling Of Biopolymerization Process Using First Principle Model And Bootstrap Re-Sampling Neural Network
by: Noor, Rabiatul 'Adawiah Mat
Published: (2011)