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《Power System Technology》 2002-04
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APPLICATION OF FUZZY LINEAR REGRESSION TO LOAD FORECASTING

GENG Guang fei, GUO Xi qing (Electric Information Institute, China Agriculture University, Beijing 100083, China)  
Linear regression analysis is a most common method for mid term load forecasting. Because of the influence of many uncertain factors, the collected historical data and the future correlative variable data are often imprecise. It leads to the notable errors in forecasting results. In order to improve the accuracy of load forecasting, an improved fuzzy linear regression model, which is also named as weighted fuzzy linear regression, is proposed in this paper. Linear programming is used to solve the fuzzy linear regression problem. The fuzzy linear regression model is improved in two aspects. The weight of each term in the object function is determined according to the importance of each regression variable. The relevant value is determined according to the importance of each historical datum. The weighted fuzzy linear regression model is adjustable. It can take some qualitative and fuzzy factors into account easily. The practical calculation shows that the forecasting precision is improved with the method mentioned above.
【CateGory Index】: TM714
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