Design of the Neural Model Structure Based on Genetic Algorithms
I. Sekaj
Slovak University of Technology in Bratislava
Abstract
Genetic algorithm based neural model structure design of a non-linear dynamic system is described. The genetic algorithm represents an optimisation procedure, where the cost function, which is minimized consists of the non-linear dynamic process neural model simulation and a selected performance index evaluation. Using this approach the neural model of the process has been optimised from point of view its internal architecture. A multilayer perceptron (MLP) artificial neural network has been used, where the training was realized by the Levenberg-Marquardt method.
Full paper
Session
Intelligent Control Systems (Poster)
Reference
Sekaj, I.: Design of the Neural Model Structure Based on Genetic Algorithms. Editors: Fikar, M., Kvasnica, M., In Proceedings of the 17th International Conference on Process Control ’09, Štrbské Pleso, Slovakia, 273–276, 2009
BibTeX
@inProceedings{pc09-043, | ||
author | = { | Sekaj, I.}, |
title | = { | Design of the Neural Model Structure Based on Genetic Algorithms}, |
booktitle | = { | Proceedings of the 17th International Conference on Process Control '09}, |
year | = { | 2009}, |
pages | = { | 273-276}, |
editor | = { | Fikar, M. and Kvasnica, M.}, |
address | = { | Štrbské Pleso, Slovakia}, |
publisher | = { | Slovak University of Technology in Bratislava}, |
url | = { | http://www.kirp.chtf.stuba.sk/pc09/data/papers/043.pdf}} |