E3S Web Conf.
Volume 124, 2019International Scientific and Technical Conference Smart Energy Systems 2019 (SES-2019)
|Number of page(s)||4|
|Published online||10 February 2020|
- Neural networks (2018) URL http://statsoft.ru/home/textbook/modules/stneunet. [Google Scholar]
- G.P. Shumilova, N.E. Gotman, T.B. Startseva, Prediction of electrical loads in the operational management of electrical energy systems based on neural network structures, 88 (2008) [Google Scholar]
- B.V. Papkov, Reliability and efficiency of power supply: tutorial, 210 (1996) [Google Scholar]
- C.E. Kuznecov, Forecasting power consumption using neural networks (2016) [Google Scholar]
- K.L. Solomakho, Use of the principal components method to predict the electricity consumption of the power supply company, 141 (2015) [Google Scholar]
- Group method if data handling (2019) https://en.wikipedia.org/wiki/GMDH [Google Scholar]
- A.M. Abdurakhmanov, M.V. Volodin, Ye.Yu. Zybin, Methods for predicting power consumption in distribution networks, 18–20 (2016) [Google Scholar]
- V.Z. Manusov, S.V. Khokhlova., Comparative analysis of two models of electrical load forecasting of industrial enterprises based on regression analysis and artificial neural networks, Scientific messenger NGTU, 1, 11–13 (2008) [Google Scholar]
- Wiener series (2019) URL https://en.wikipedia.org/wiki/Wiener_series [Google Scholar]
- N.A. Serebryakov, S.O. Khomutov, Improving the quality of short-term electrical load forecasting for a group of points of supply for agricultural producers Using a multi-layer perceptron, 90 (2016) [Google Scholar]
- System Operator of the Unified Energy System (2019) URL https://so-ups.ru/ [Google Scholar]
- I.Yu. Alekseyeva, Improving the reliability of electric power systems based on neural technologies, 15 (2016) [Google Scholar]
- Group method of data handling (2019) URL http://www.gmdh.net/ [Google Scholar]
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