Abstract
Original language | English |
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Title of host publication | Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08 |
Publisher | IEEE |
Pages | 311-317 |
Number of pages | 7 |
ISBN (Print) | 9780769534954 |
DOIs | |
Publication status | Published - 11 Dec 2008 |
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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
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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
AU - Nguyen, Hang T.
AU - Nabney, Ian T.
N1 - Seventh International Conference on Machine Learning and Applications, San Diego (US)
PY - 2008/12/11
Y1 - 2008/12/11
N2 - 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.
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.
KW - forecasting theory
KW - natural gas technology
KW - power markets
KW - power system economics
KW - pricing
KW - wavelet transforms
KW - UK gas market
KW - electricity load
KW - forecasting model
KW - forward energy price
KW - gas forward price prediction
KW - gas load
KW - market clearing price forecasting
KW - wavelet transform
KW - GARCH
KW - linear regression
KW - multi-layer perceptron
UR - http://www.scopus.com/inward/record.url?scp=60649103358&partnerID=8YFLogxK
U2 - 10.1109/ICMLA.2008.37
DO - 10.1109/ICMLA.2008.37
M3 - Chapter
SN - 9780769534954
SP - 311
EP - 317
BT - Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08
PB - IEEE
ER -