A Comparative Study of ARIMA, RBFNN, and Hybrid RBFNNARIMA Models for Electricity Net Consumption Forecasting in Algeria
30 juin 2024
À propos de cet article
Publié en ligne: 30 juin 2024
Pages: 189 - 198
Reçu: 18 mars 2024
Accepté: 19 mai 2024
DOI: https://doi.org/10.19275/rsep185
Mots clés
© 2024 Hacen Kahoui et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
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.