Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/69276
Title: Artificial intelligence in electricity market operations and management
Authors: Dong, ZY
Saha, TK
Wong, KP 
Issue Date: 2006
Publisher: Idea Group Pub.
Source: In KE Voges & NKL Pope (Eds.), Business applications and computational intelligence, p. 131-154. Hershey, PA: Idea Group Pub., 2006 How to cite?
Abstract: This chapter introduces advanced techniques such as artificial neural networks, wavelet decomposition, support vector machines, and data-mining techniques in electricity market demand and price forecasts. It argues that various techniques can offer different advantages in providing satisfactory demand and price signal forecast results for a deregulated electricity market, depending on the specific needs in forecasting. Furthermore, the authors hope that an understanding of these techniques and their application will help the reader to form a comprehensive view of electricity market data analysis needs, not only for the traditional time-series based forecast, but also the new correlation-based, price spike analysis.
URI: http://hdl.handle.net/10397/69276
ISBN: 1591407044 (electronic bk.)
1591407036 (softcover)
1591407028 (hardcover)
Appears in Collections:Book Chapter

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