Anderson Paulo da Silva,  Teresa Ludermir,  Leandro Maciel Almeida. 

This paper describes an automatic search method, CGANN-DC (Cellular Genetic Algorithm + Neural Networks - Direct enCod), for Artificial Neural Networks (ANNs) using Cellular Genetic Algorithms (CGAs). The mais difference between CGAs and Genetic Algorithms (GAs) is the use of a cellular automaton (CA) capable of providing the location for individuals, reducing the possibility of local minima in search space. The CGANN-DC performs evolutionary searches for initial weights, transfer functions, architectures and learning rules. Experimental results have shown that CGANN-DC can find compact networks with a satisfactory generalization power.

http://www.lbd.dcc.ufmg.br/colecoes/enia/2011/0052.pdf

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