DocumentCode
3038314
Title
Neural network construction using grammatical evolution
Author
Tsoulos, Ioannis G. ; Gavrilis, Dimitris ; Glavas, Euripidis
Author_Institution
Dept. of Comput. Sci., Ioannina Univ.
fYear
2005
fDate
21-21 Dec. 2005
Firstpage
827
Lastpage
831
Abstract
A method which is based on grammatical evolution is presented in this paper for the construction of artificial neural networks (ANNs). The method is capable to construct ANNs with an arbitrary number of hidden levels or even recurrent neural networks. The efficiency of the method is tested on a series of classification and regression problems and the results are compared against traditional neural networks
Keywords
artificial intelligence; genetic algorithms; neural net architecture; recurrent neural nets; artificial neural networks; grammatical evolution; neural network construction; recurrent neural networks; Artificial neural networks; Biological cells; Computer network management; Computer networks; Computer science; Informatics; Neural networks; Signal processing algorithms; Technology management; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Information Technology, 2005. Proceedings of the Fifth IEEE International Symposium on
Conference_Location
Athens
Print_ISBN
0-7803-9313-9
Type
conf
DOI
10.1109/ISSPIT.2005.1577206
Filename
1577206
Link To Document