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- W3156608801 abstract "Due to the influence of many factors in power grid, the prediction accuracy of line loss rate is not high and it’s applicability is poor. To solve this problem, a line loss rate prediction model based on density clustering and ensemble method is proposed. 18 characteristics related to distribution network in 2019 are selected as independent variables, and comprehensive line loss rate in 2019 is taken as dependent variable. The DBSCAN clustering algorithm is used to cluster the data set, and the random forest and LR- Bagging are used to predict each type of data respectively, and a combined line loss rate prediction model is established. The experimental results show that the prediction accuracy and universality of line loss rate can be effectively improved after the processing of clustering algorithm and a variety of integrated prediction methods." @default.
- W3156608801 created "2021-04-26" @default.
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- W3156608801 date "2021-03-12" @default.
- W3156608801 modified "2023-10-17" @default.
- W3156608801 title "Research on line loss prediction model based on clustering and multi prediction model fusion" @default.
- W3156608801 cites W3087520226 @default.
- W3156608801 doi "https://doi.org/10.1109/iaeac50856.2021.9390604" @default.
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