A new encoding method for optimizing neural network structures is proposed. It is based on an indirect encoding method with variable length gene code. The search ability for finding an optimal solution is higher than the direct encoding methods because redundant information in gene code is reduced and the search space is also reduced. The proposed method easily operates adding and deleting hidden units. The performance of the proposed method is evaluated through computer simulations.
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