BMF fuzzy neural network with genetic algorithm for forecasting electric load

Yuang Shung Lee*, Chia Hui Kao, Wei Yen Wang

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

2 引文 斯高帕斯(Scopus)

摘要

Electricity is widely applied in many aspects of modern life. Precise forecasting of electricity consumption may not only reduce operational and maintenance cost for power companies but also enhance the reliability of power supply systems, as well as avoid shortage of supply that causes damage and inconvenience to customers. In this paper, load forecasting is facilitated by a so-called BMF Fuzzy neural network, which features a structure adjusted by genetic algorithm. The purpose is to obtain better control points and weights, so as to ensure sound performance. Seven networks are constructed in correspondence with the seven different electrical loading models from Monday to Sunday. Results of the simulation reflect the forecasted loading in winter and summer months.

原文英語
主出版物標題Proceedings of the International Conference on Power Electronics and Drive Systems
頁面1662-1666
頁數5
出版狀態已發佈 - 2005 十二月 1
事件Sixth International Conference on Power Electronics and Drive Systems, PEDS 2005 - Kualu Lumpur, 马来西亚
持續時間: 2005 十一月 282005 十二月 1

出版系列

名字Proceedings of the International Conference on Power Electronics and Drive Systems
2

其他

其他Sixth International Conference on Power Electronics and Drive Systems, PEDS 2005
國家/地區马来西亚
城市Kualu Lumpur
期間2005/11/282005/12/01

ASJC Scopus subject areas

  • 電氣與電子工程

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