| Autor: |
Rakhmonov I.U., Niyozov N.N., Kurbonov N.N., Umarov B.S. |
| Jazyk: |
English<br />French |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
E3S Web of Conferences, Vol 384, p 01030 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2267-1242 |
| DOI: |
10.1051/e3sconf/202338401030 |
| Popis: |
The development of models for forecasting electricity consumption is a complex process, due to the non-linear dependence of electricity consumption on factors that affect the forecast indicators. Since the current forecasting methods do not take into account this non-linearity, the difference between the actual and forecast indicators of electricity consumption often exceeds the allowable values. To determine the required forecast indicators with high accuracy is the use of artificial intelligence methods. In this paper, when predicting electricity consumption, the method of autoregression of the integrated moving average is used. An enlarged block diagram of the algorithm for predicting power consumption using the ARIMA method has been developed. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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