An Evolutionary Method to Find Good Building-Blocks for Architectures of Artificial Neural Networks (1996) [10 citations — 1 self]
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author = {Christoph M. Friedrich and Alfred-herrhausen Str and Claudio Moraga},
title = {An Evolutionary Method to Find Good Building-Blocks for Architectures of Artificial Neural Networks},
year = {1996}
}
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Abstract:
This paper deals with the combination of Evolutionary Algorithms and Artificial Neural Networks (ANN). A new method is presented, to find good building-blocks for architectures of Artificial Neural Networks. The method is based on Cellular Encoding, a representation scheme by F. Gruau, and on Genetic Programming by J. Koza. First it will be shown that a modified Cellular Encoding technique is able to find good architectures even for non-boolean networks. With the help of a graph-database and a new graph-rewriting method, it is secondly possible to build architectures from modular structures. The information about buildingblocks for architectures is obtained by statistically analyzing the data in the graphdatabase. Simulation results for two realworld problems are given. 1 Introduction One of the major problems using ANN's is the design of their architecture. The architecture of an ANN greatly influences its performance. If the architecture is too small, the net is not able to learn t...
