A Comparative Study of ARIMA, RBFNN, and Hybrid RBFNNARIMA Models for Electricity Net Consumption Forecasting in Algeria

Kahoui, Hacen; Chekouri, Sidi Mohammed; Sahed, Abdelkader

doi:10.19275/rsep185

Abstract

This study aims to compare the performance of three different forecasting methods for electricity consumption such as ARIMA, RBFNN, and hybrid RBFNN-ARIMA in Algeria over the period from 1990 to 2030. The results show that the RBFNN model outperforms the other two models in terms of accuracy. The RBFNN model is able to capture the nonlinear relationships in the data and is more robust to noise than the other models. The findings of this study have important implications for energy planning and management in Algeria. The RBFNN model can be used to develop more accurate and reliable forecasts of electricity net consumption, which can help to improve the efficiency of energy planning and management.

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A Comparative Study of ARIMA, RBFNN, and Hybrid RBFNNARIMA Models for Electricity Net Consumption Forecasting in Algeria

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