COMPARATIVE STUDY OF ARIMA AND ARTIFICIAL NEURAL NETWORK METHODS FOR IRAN ELECTRICITY FORECASTING

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AHMADI ALI MOHAMMAD; ZOLFAGHART MAHDI; GHAFAMEZHAD MEHRABANT AIDIN

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Journal: Iranian Journal of Economic Research Year:2010 | Volume:13 | Issue:41 Page(s): 107-121

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Title

COMPARATIVE STUDY OF ARIMA AND ARTIFICIAL NEURAL NETWORK METHODS FOR IRAN ELECTRICITY FORECASTING

Author(s)

AHMADI ALI MOHAMMAD | ZOLFAGHART MAHDI | GHAFAMEZHAD MEHRABANT AIDIN | Issue Writer Certificate

Keywords

NEURAL NETWORKQ2

ARIMAQ2

FORECASTQ2

ELECTRICITY DOMESTIC REQUIREMENTQ3

Abstract

Electricity demand is growing very fast in Iran and it is important to FORECAST its future demand and its monthly variation accurately.Artificial NEURAL NETWORK (ANN) is a powerful tool for nonlinear models for FORECASTing and it was used to estimate monthly electricity demand in this study. In this paper, we compared the Non-linear ANN model with ARIMA linear model to estimate monthly electricity demand for a priod of 3 years. Using MSE, RMSE, NMSE, MHE, MAPE and R2 indicatorss, our results show that ANN FORECASTing model is superior to ARIMA in terms of less error coefficient and high explanatory ability.

Cites

COMPARISON OF NEURAL NETWORKS AND ARIMA IN MODELING AND FORECASTING OF SHORT RUN PRICING OF THE OPEC CRUDE OIL BASKET (WITH FOCUS ON COMPARATIVE EXPECTATIONS)

References

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APA: Copy

AHMADI, ALI MOHAMMAD, ZOLFAGHART, MAHDI, & GHAFAMEZHAD MEHRABANT, AIDIN. (2010). COMPARATIVE STUDY OF ARIMA AND ARTIFICIAL NEURAL NETWORK METHODS FOR IRAN ELECTRICITY FORECASTING. IRANIAN ECONOMIC RESEARCH, 13(41), 107-121. SID. https://sid.ir/paper/2512/en

Vancouver: Copy

AHMADI ALI MOHAMMAD, ZOLFAGHART MAHDI, GHAFAMEZHAD MEHRABANT AIDIN. COMPARATIVE STUDY OF ARIMA AND ARTIFICIAL NEURAL NETWORK METHODS FOR IRAN ELECTRICITY FORECASTING. IRANIAN ECONOMIC RESEARCH[Internet]. 2010;13(41):107-121. Available from: https://sid.ir/paper/2512/en

IEEE: Copy

ALI MOHAMMAD AHMADI, MAHDI ZOLFAGHART, and AIDIN GHAFAMEZHAD MEHRABANT, “COMPARATIVE STUDY OF ARIMA AND ARTIFICIAL NEURAL NETWORK METHODS FOR IRAN ELECTRICITY FORECASTING,” IRANIAN ECONOMIC RESEARCH, vol. 13, no. 41, pp. 107–121, 2010, [Online]. Available: https://sid.ir/paper/2512/en

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