DocumentCode
734449
Title
Optimization of parameters of neural networks by genetic algorithm in the control systems of electromechanical objects
Author
Belov, M.P. ; Zolotov, O.I.
Author_Institution
St. Petersburg Electrotech. Univ. "LETI", St. Petersburg, Russia
fYear
2015
fDate
19-21 May 2015
Firstpage
136
Lastpage
138
Abstract
This study investigates the effectiveness of the genetic algorithm evolved neural network and its application in the drive control systems of electromechanical objects. The methodology adopts a real coded GA strategy using datasets in a series of experiments that evaluate the effects on network performance of different choices of network parameters.
Keywords
genetic algorithms; neurocontrollers; paper making machines; rolling mills; control systems; electromechanical objects; genetic algorithm evolved neural network; network parameters; network performance; parameters optimization; real coded GA strategy; Biological cells; Biological neural networks; Genetic algorithms; Neurons; Reactive power; Sociology; Statistics; control systems; electromechanical objects; genetic algorithm; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Soft Computing and Measurements (SCM), 2015 XVIII International Conference on
Conference_Location
St. Petersburg
Print_ISBN
978-1-4673-6960-2
Type
conf
DOI
10.1109/SCM.2015.7190490
Filename
7190490
Link To Document