Hybrid neural network and fuzzy logic methods for implementation of equipment actual state assessment of power stations and substations

Alexandra I. Khalyasmaa, Stepan A. Dmitriev, Andrey A. Verxozin, and Sergei F. Sarapulov

Keywords

Assessment of power equipment actual state, TakagiSugeno algorithm, BellmanZadeh scheme, training sample, statistical data

Abstract

The article is concerned with problems of expert systems development and implementation for power equipment actual state assessment on power stations and substations on the base of hybrid neural networks. The article covers analysis of training sample data influence on results of power equipment actual state assessment with the use of different statistical criterion.

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