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

Hang T. Nguyen, Ian T. Nabney

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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.
Original languageEnglish
Title of host publicationSeventh International Conference on Machine Learning and Applications, 2008. ICMLA '08
PublisherIEEE
Pages311-317
Number of pages7
ISBN (Print)9780769534954
DOIs
Publication statusPublished - 11 Dec 2008

Fingerprint

Wavelet transforms
Gases
Multilayer neural networks
Linear regression
Electricity

Bibliographical note

Seventh International Conference on Machine Learning and Applications, San Diego (US)

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

Cite this

Nguyen, H. T., & Nabney, I. 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 (pp. 311-317). IEEE. https://doi.org/10.1109/ICMLA.2008.37
Nguyen, Hang T. ; Nabney, Ian T. / Combining the wavelet transform and forecasting models to predict gas forward prices. Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08. IEEE, 2008. pp. 311-317
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Nguyen, HT & Nabney, IT 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, pp. 311-317. https://doi.org/10.1109/ICMLA.2008.37

Combining the wavelet transform and forecasting models to predict gas forward prices. / Nguyen, Hang T.; Nabney, Ian T.

Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08. IEEE, 2008. p. 311-317.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

TY - CHAP

T1 - Combining the wavelet transform and forecasting models to predict gas forward prices

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AB - 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.

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KW - natural gas technology

KW - power markets

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KW - pricing

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KW - electricity load

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BT - Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08

PB - IEEE

ER -

Nguyen HT, Nabney IT. 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. 2008. p. 311-317 https://doi.org/10.1109/ICMLA.2008.37

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    Seventh International Conference on Machine Learning and Applications, San Diego (US)