The evolutionary approach for neural network structural synthesis is considered in this paper. The new method of multimodal evolutionary search with a chromosome clustering is offered. The developed method is based on the idea of simultaneous search of several optimums, thus chromosomes are grouped in clusters on their arrangement in a search space. So stable subpopulations in different clusters are formed, diversity of search is provided, and convergence to different local minima is reached that allows to find closer to optimal architectures of neural networks. Software implementing proposed method is developed. The experiments with proposed method in practical problem solving were conducted.

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