System for forecasting energy consumption using the artificial neural network
Автор: Abramovich Boris N., Babanova Irina S.
Журнал: Горные науки и технологии @gornye-nauki-tekhnologii
Рубрика: Энергетика, автоматизация и энергоэффективность
Статья в выпуске: 2, 2016 года.
Бесплатный доступ
The article considers the possibility of increasing the efficiency of the mining enterprise at the expense of correct choice of price categories and tariff for electricity. The efficiency of forecasting model of energy consumption by the rational choice of price categories is shown, a system for predicting energy consumption using artificial neural network is developed. The forecast error is 0.908 % with the architecture of the network type MLP (MLP 24-18-1)
Energy management, artificial neural network, electricity tariff, price category, intelligent metering system, error prediction, architecture network, multilayer perceptron
Короткий адрес: https://sciup.org/140215869
IDR: 140215869
