Title :
Neural network construction using grammatical evolution
Author :
Tsoulos, Ioannis G. ; Gavrilis, Dimitris ; Glavas, Euripidis
Author_Institution :
Dept. of Comput. Sci., Ioannina Univ.
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;
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
DOI :
10.1109/ISSPIT.2005.1577206
