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Proceedings Paper

Gas demand forecasting by a new artificial intelligent algorithm
Author(s): Vahid Khatibi.B; Elham Khatibi
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Paper Abstract

Energy demand forecasting is a key issue for consumers and generators in all energy markets in the world. This paper presents a new forecasting algorithm for daily gas demand prediction. This algorithm combines a wavelet transform and forecasting models such as multi-layer perceptron (MLP), linear regression or GARCH. The proposed method is applied to real data from the UK gas markets to evaluate their performance. The results show that the forecasting accuracy is improved significantly by using the proposed method.

Paper Details

Date Published: 14 January 2012
PDF: 6 pages
Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 83492P (14 January 2012); doi: 10.1117/12.920305
Show Author Affiliations
Vahid Khatibi.B, Islamic Azad Univ. (Iran, Islamic Republic of)
Elham Khatibi, Islamic Azad Univ. (Iran, Islamic Republic of)


Published in SPIE Proceedings Vol. 8349:
Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis
Zhu Zeng; Yuting Li, Editor(s)

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