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《Central China Electric Power》 2006-04
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Short-term Load Forecasting in Power System Based on Adaptive Neuro-Fuzzy Inference System

YANG Fan1,WU Yao-wu1,XIONG Xin-yin1,LOU Su-hua1,PENG Feng2(1.College of Electrical Engineering,Huazhong University of Science and Technology,Wuhan 430074,China;2.Wuhan Power Supply Company,Wuhan 430013,China)  
An Adpative Neuro-Fuzzy Inference System based on T-S model is presented in this paper.ANFIS is initialized by subtractive clustering and neuro network is applied to Fuzzy Inference,and adjusts the parameter of the fuzzy inference system with hybrid algorithm and can produce fuzzy rules automatically.This paper gives the 2005′s summer load data of wuhan city to train and check the network,the results show the validity of short-term load forecasting based on ANFIS.
【CateGory Index】: TM715
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