DEVELOPING COMBINED FORECASTING MODELS IN OIL INDUSTRY - A Case Study in Opec Oil Demand

Seyed Hamid Khodadad Hosseini, Adel Azar, Ali Rajabzadeh Ghatari, Arash Bahrammirzaee

2011

Abstract

The purpose of this research is to study the combined forecasting methods in energy section. This method is a new approach which leads to considerable reduction of error in forecasting results. In this study, forecasting has been done through using individual methods (these methods consist of exponential smoothing methods, trend analysis, box-Jenkins, causal analysis, and neural network models) and also combining methods. In next step, the Results of these individual forecasting methods have been combined and compared with artificial neural networks, and multiple regression models. The data we used in this study are: dependent variable: OPEC oil demands from 1960 to 2005, and independent variables: oil price, GDP, other energy demands, population, and added-value in industry (in OECD countries. Computed indexes of errors are: MSE, MAPE, and GAPE which show considerable reductions in the errors of forecasting when using combining models. Therefore, it is suggested that the designed models could be applied for oil demand forecasting.

Paper Citation

in Harvard Style

Khodadad Hosseini S., Azar A., Rajabzadeh Ghatari A. and Bahrammirzaee A. (2011). DEVELOPING COMBINED FORECASTING MODELS IN OIL INDUSTRY - A Case Study in Opec Oil Demand . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 205-210. DOI: 10.5220/0003681702050210

in Bibtex Style

@conference{ncta11,
author={Seyed Hamid Khodadad Hosseini and Adel Azar and Ali Rajabzadeh Ghatari and Arash Bahrammirzaee},
title={DEVELOPING COMBINED FORECASTING MODELS IN OIL INDUSTRY - A Case Study in Opec Oil Demand},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)},
year={2011},
pages={205-210},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003681702050210},
isbn={978-989-8425-84-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)
TI - DEVELOPING COMBINED FORECASTING MODELS IN OIL INDUSTRY - A Case Study in Opec Oil Demand
SN - 978-989-8425-84-3
AU - Khodadad Hosseini S.
AU - Azar A.
AU - Rajabzadeh Ghatari A.
AU - Bahrammirzaee A.
PY - 2011
SP - 205
EP - 210
DO - 10.5220/0003681702050210