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
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;
Conference_Titel :
Soft Computing and Measurements (SCM), 2015 XVIII International Conference on
Conference_Location :
St. Petersburg
Print_ISBN :
978-1-4673-6960-2
DOI :
10.1109/SCM.2015.7190490
