Design of Short-Term Load Forecasting Model Based on Fuzzy Neural Networks

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外文摘要：According to the non-linear relation characteristic of load， a short-term load forecasting model based on fuzzy neural networks was presented。 In the model， fuzzy inference and defuzzification were completed by neural networks， and the neural networks weight values were given definite knowledge meaning。 The membership function of fuzzy layer was selected to translate the input variables of load into fuzzy variables。 Then a new inference algorithm was discussed to finish fuzzy inference。 Finally， the forecasting load values were obtained by proper defuzzification。 The simulation results show preferable forecasting capability of the model。

外文关键词：

short-term load forecastingfuzzy inferenceneural networks

作者：

Kuihe Yang、Jinjun Zhu、Baoshu Wang、Lingling Zhao

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作者单位：

Xidian University Xi'an China

会议名称：

Fifth World Congress on Intelligent Control and Automation(WCICA 2004) vol.3

会议地点：

Hangzhou(CN)

会议母体文献：

World Congress on Intelligent Control and Automation(WCICA 2004) vol.3; 20040615-19; Hangzhou(CN)

页码：

P.2038-2041

出版时间：

2004