Electricity market forecasting using artificial neural network models optimized by grid computing

Aishah Mohd Isa, Takahide Niimura, Noriaki Sakamoto, Kazuhiro Ozawa, Ryuichi Yokoyama

研究成果: Article査読

2 被引用数 (Scopus)

抄録

This paper reports a grid computing approach to parallel-process a neural network time-series model for forecasting electricity market prices. The grid computing of the neural network model not only processes several times faster than a single iterative process but also provides chances of improving forecasting accuracy. A grid-computing environment implemented in a university computing laboratory improves utilization rate of otherwise underused computing resources. Results of numerical tests using the real market data by more than twenty grid-connected PCs are presented.

本文言語English
ページ(範囲)273-277
ページ数5
ジャーナルUnknown Journal
出版ステータスPublished - 2009

ASJC Scopus subject areas

  • 制御およびシステム工学

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