Neural network construction using grammatical evolution
Ioannis G. Tsoulos, Dimitris Gavrilis, Euripidis Glavas · 2006
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