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SYNTHESIS OF OPTIMAL ARTIFICIAL NEURAL NETWORKS BY MODIFIED GENETIC ALGORITHM

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  Principles of neural networks synthesis are considered, shortcomings of approaches are shown when choosing the structure and scales adjustment. Networks optimization is possible by evolutionary algorithms application with advantages becoming apparent with multi coherent and multilayered networks operation. Simulation experiments were made on concrete test function and confirm efficiency of the developed algorithms.

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