DocumentCode :
1615800
Title :
Genetic algorithms to select optimal neural network topology
Author :
Arena, P. ; Caponetto, R. ; Fortuna, L. ; Xibilia, M.G.
Author_Institution :
Dipartimento Elettrico Elettronico e Sistemistico, Catania Univ., Italy
fYear :
1992
Firstpage :
1381
Abstract :
The choice of the optimal topology for a multilayer perceptron neural network is considered by using genetic algorithms (GAs). The proposed strategy is intended both to select the number of neurons in a structure with one hidden layer and to choose the number of layers into which a fixed number of neurons should be optimally arranged to solve a given problem. The proposed GA has shown its suitability in determining efficiently the optimal topology of a neural network. The procedure is not time consuming and is able to easily take into account all the constrains eventually included in the problem
Keywords :
feedforward neural nets; genetic algorithms; network topology; genetic algorithms; multilayer perceptron neural network; optimal topology; Biological cells; Constraint theory; Genetic algorithms; Monitoring; Multi-layer neural network; Multilayer perceptrons; Network topology; Neural networks; Neurons; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1992., Proceedings of the 35th Midwest Symposium on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-0510-8
Type :
conf
DOI :
10.1109/MWSCAS.1992.271082
Filename :
271082
Link To Document :
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