Evolving Recurrent Neural Networks with Non binary Encoding

Martin Mandischer
Systems Analysis Research Group
Department of Computer Science
University of Dortmund
Dortmund Germany

This paper presents an evolutionary approach for the design of feed forward and recurrent neural networks We show that Evolutionary Algorithms can be used for the construction of networks for real world tasks Therefore a data structure based genotypic network representation as well as genetic operators are introduced Results from the classification function approximation and time series domain are presented.

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