Determining the architecture of a neural network in the problem of estimating the state of the battery charge

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Abstract

The problem of estimating the state of charge of the battery, based on neural networks, is considered. Two types of recurrent nonlinear autoregressive neural networks were investigated in the problem of estimating the state of charge of a battery during its use. The main criterion for the quality of forecasting was the mean square error. According to the results of the study, the optimal structure of the neural network was chosen.

About the authors

Ilya Andreevich Yakovlev

Ufa State Aviation Technical University

Author for correspondence.
Email: ilya-yakovlev-1999@bk.ru
Ufa

Anastasia Valer'evna Elizarova

Ufa State Aviation Technical University

Email: elizarovaanastasia@gmail.com
Ufa

Guzel Askhatovna Saitova

Ufa State Aviation Technical University

Email: saitova@bk.ru
Ufa

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