Abstract
The problem of training neuro-fuzzy networks is discussed. The computational complexity of the method for training neuro-fuzzy networks on the basis of parallel random search is analyzed. Theoretical estimations of the speedup and efficiency of the method are found. Software implementing of the method in C++ with using the MPI library and providing the construction of neuro-fuzzy networks in terms of the given observation sets is developed. Experiments for practical tasks are carried out.
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Original Russian Text © A.O. Oliinyk, S.Yu. Skrupsky, S.A. Subbotin, 2015, published in Avtomatika i Vychislitel’naya Tekhnika, 2015, No. 1, pp. 18–30.
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Oliinyk, A.O., Skrupsky, S.Y. & Subbotin, S.A. Experimental investigation with analyzing the training method complexity of neuro-fuzzy networks based on parallel random search. Aut. Control Comp. Sci. 49, 11–20 (2015). https://doi.org/10.3103/S0146411615010071
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DOI: https://doi.org/10.3103/S0146411615010071