Electricity Consumption Forecast Based on Neural Networks

Uakhitova, Aigul

doi:10.1134/s2070048222050167

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2023

2024

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Cited by 5 publications

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“…In recent decades, the application of the theory of artificial intelligence in forecasting has been widely used. Electrical load prediction methods based on artificial neural networks (ANNs) have shown the best results in a number of studies [3].…”

Section: Introductionmentioning

confidence: 99%

Short-Term Electrical Load Forecasting Based on Neural Networks

Kuantayev

Bainiyazov²,

Uakhitova³

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The article sets out the use of an artificial neural network for electrical load consumption forecasting. Electrical load prediction is one of the most demanded areas of research in the electric power industry. The two-layer artificial neural network of direct distribution with the number of neurons in the hidden layer equal to 6 was proposed in the article. The following data was taken as an input for forecasting short-term electrical load: electrical load, time, day of the week, temperature, day, weekend and working day code. According to the studies, the value of the mean absolute percentage error was 2.35, using the Bayesian Regularization learning algorithm.

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Section: Introductionmentioning

confidence: 99%