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《Proceedings of the Chinese Society of Universities for Electric Power System and Automation》 2007-01
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Fuzzy Neural Network Model Based on Particle Swarm Optimization for Short-term Load Forecasting

WU Jie-kang1,CHEN Ming-hua1,CHEN Guo-tong2(1.School of Electrical Engineering,Guangxi University,Nanning 530004,China;2.Guangxi Wuzhou Electric Power Company,Wuzhou 543002,China)  
According to the trait of power load,this paper proposes a PSO based fuzzy neural network model for short-term load forecasting.The model makes full use of the global optimization of PSO and local accurate searching of BP.Practical example indicates that the application of PSO~FNN to short-term load forecasting is feasible and effective,which can obtain more accurate result than conventional methods.
【Fund】: 广西科学基金资助项目(桂科自0640028);; 宁波市自然科学基金资助项目(2005A610013);; 广西壮族自治区教育厅资助项目;; 广西壮族自治区科技厅科技计划资助项目
【CateGory Index】: TM715
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