DocumentCode :
3209790
Title :
Evolutionary design of ANN structure using genetic algorithm
Author :
Moharamzade, N. ; Farokhi, F.
Author_Institution :
Sci. Assoc. of Electr. & Electron. Eng., Islamic Azad Univ., Tehran, Iran
Volume :
2
fYear :
2010
fDate :
13-14 Sept. 2010
Firstpage :
219
Lastpage :
224
Abstract :
Determining the optimum structure for an Artificial Network is an important design step in almost all the artificial intelligence systems which are based on Neural or neuro-fuzzy networks. In this paper a genetic algorithm based solution is presented and tested over real world databases and for single layer and multiple layer networks and it has been shown that the determined network structures has the best accuracy and the optimized topology as well.
Keywords :
fuzzy neural nets; genetic algorithms; multilayer perceptrons; artificial intelligence system; evolutionary ANN structure design; genetic algorithm; multiple layer network; neuro-fuzzy network; single layer network; Computational intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Natural Computing Proceedings (CINC), 2010 Second International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7705-0
Type :
conf
DOI :
10.1109/CINC.2010.5643748
Filename :
5643748
Link To Document :
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