Gas Demand Forecasting By a New Artificial Intelligent Algorithm

被引：0

作者：

Khatibi, Vahid B. ^{[1
]}

Khatibi, Elham ^{[1
]}

机构：

[1] Islamic Azad Univ, Bardsir Branch, Kerman, Iran

来源：

FOURTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2011): MACHINE VISION, IMAGE PROCESSING, AND PATTERN ANALYSIS | 2012年 / 8349卷

关键词：

Wavelet Transform; Multilayer Perceptron (MLP); Forecast Method; Gas Demand; ELECTRICITY PRICES; WAVELET TRANSFORM;

D O I：

10.1117/12.920305

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页数：6

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