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Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 8 Issue 6 pp. 581-592 , 2018

Nonlinear ARIMAX model for long –term sectoral demand forecasting Pages 581-592 Right click to download the paper Download PDF

Authors: Najmeh Neshat, Hengameh Hadian, Matineh Behzad

DOI: 10.5267/j.msl.2018.4.032

Keywords: Nonlinear Forecasting Model, Times-Series Analysis, Peak Demand

Abstract: With the rapid increase of energy demand, it is becoming increasingly important to obtain accurate energy demand forecasts. To incorporate long time causal relationships, autoregressive with exoge-nous regression components models have received increasing attention from many researchers in this field. These are linear models applied through hybrid methodology of time series and econo-metrics, however, some recent studies find evidences that nonlinear models outperform over linear ones in long term peak demand forecasting. This paper proposed a nonlinear Auto Regressive Integrated Moving Average with Exogenous Inputs (N-ARIMAX) model to forecast sectoral peak demand using a case study of Iran. The results indicate that significant improvements in forecasting accuracy are obtained with the proposed models compared to the existing models.

How to cite this paper
Neshat, N., Hadian, H & Behzad, M. (2018). Nonlinear ARIMAX model for long –term sectoral demand forecasting.Management Science Letters , 8(6), 581-592.

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Journal: Management Science Letters | Year: 2018 | Volume: 8 | Issue: 6 | Views: 2599 | Reviews: 0

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