Combining the wavelet transform and forecasting models to predict gas forward prices

Nguyen, Hang T. and Nabney, Ian T. (2008). Combining the wavelet transform and forecasting models to predict gas forward prices. IN: Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08. IEEE.

Abstract

This paper presents a forecasting technique for forward energy prices, one day ahead. This technique combines a wavelet transform and forecasting models such as multi- layer perceptron, linear regression or GARCH. These techniques are 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 wavelet transform. The methodology can be also applied to forecasting market clearing prices and electricity/gas loads.

Publication DOI: https://doi.org/10.1109/ICMLA.2008.37
Divisions: Engineering & Applied Sciences > Computer Science
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Additional Information: Seventh International Conference on Machine Learning and Applications, San Diego (US)
Uncontrolled Keywords: forecasting theory,natural gas technology,power markets,power system economics,pricing,wavelet transforms,UK gas market,electricity load,forecasting model,forward energy price,gas forward price prediction,gas load,market clearing price forecasting,wavelet transform,GARCH,linear regression,multi-layer perceptron,Artificial Intelligence,Computer Science Applications,Software
Full Text Link: http://ieeexplo ... ld%3DSearch+All
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Published Date: 2008-12-11
Authors: Nguyen, Hang T.
Nabney, Ian T. ( 0000-0003-1513-993X)

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