An empty-nest power user identification method based on weighted random forest algorithm
In view of the lack of effective technical means for the identification of empty-nesters by the government and the society,an empty-nesters prow user identification method based on weighted random forest algorithm was proposed.Firstly,some accurate labels of empty-nest users were obtained through qu...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2020-08-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020249/ |
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| _version_ | 1841529043730563072 |
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| author | Zimeng LU Jiayi CHEN Jing LI Yue XIE Xinli JIANG Lei HAN Qian GUO |
| author_facet | Zimeng LU Jiayi CHEN Jing LI Yue XIE Xinli JIANG Lei HAN Qian GUO |
| author_sort | Zimeng LU |
| collection | DOAJ |
| description | In view of the lack of effective technical means for the identification of empty-nesters by the government and the society,an empty-nesters prow user identification method based on weighted random forest algorithm was proposed.Firstly,some accurate labels of empty-nest users were obtained through questionnaires,and electricity characteristic library was drawn from three aspects:electricity consumption level,electricity consumption fluctuation and electricity consumption trend.Due to the data imbalance between empty-nest and non-empty-nest users,the weighted random forest algorithm was used to improve the data sensitivity phenomenon of machine learning.Finally,the algorithm model was put online in the power company’s acquisition system.The 2 000 unknown users of various types were identified,among which the identification accuracy of empty-nest users was 74.2%.The results show that the identification of empty-nesters from the perspective of electricity consumption can help power grid companies to understand the personalized and differentiated needs of empty-nesters,so as to provide users with more sophisticated services,and also assist the government and society to carry out assistance work. |
| format | Article |
| id | doaj-art-bf3d9eeaa4194aa192ca71616e6c0bf5 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2020-08-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-bf3d9eeaa4194aa192ca71616e6c0bf52025-01-15T03:27:26ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012020-08-013611212159811804An empty-nest power user identification method based on weighted random forest algorithmZimeng LUJiayi CHENJing LIYue XIEXinli JIANGLei HANQian GUOIn view of the lack of effective technical means for the identification of empty-nesters by the government and the society,an empty-nesters prow user identification method based on weighted random forest algorithm was proposed.Firstly,some accurate labels of empty-nest users were obtained through questionnaires,and electricity characteristic library was drawn from three aspects:electricity consumption level,electricity consumption fluctuation and electricity consumption trend.Due to the data imbalance between empty-nest and non-empty-nest users,the weighted random forest algorithm was used to improve the data sensitivity phenomenon of machine learning.Finally,the algorithm model was put online in the power company’s acquisition system.The 2 000 unknown users of various types were identified,among which the identification accuracy of empty-nest users was 74.2%.The results show that the identification of empty-nesters from the perspective of electricity consumption can help power grid companies to understand the personalized and differentiated needs of empty-nesters,so as to provide users with more sophisticated services,and also assist the government and society to carry out assistance work.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020249/empty-nest user identificationweighted random forest algorithmuser electricity characteristic librarydata imbalance |
| spellingShingle | Zimeng LU Jiayi CHEN Jing LI Yue XIE Xinli JIANG Lei HAN Qian GUO An empty-nest power user identification method based on weighted random forest algorithm Dianxin kexue empty-nest user identification weighted random forest algorithm user electricity characteristic library data imbalance |
| title | An empty-nest power user identification method based on weighted random forest algorithm |
| title_full | An empty-nest power user identification method based on weighted random forest algorithm |
| title_fullStr | An empty-nest power user identification method based on weighted random forest algorithm |
| title_full_unstemmed | An empty-nest power user identification method based on weighted random forest algorithm |
| title_short | An empty-nest power user identification method based on weighted random forest algorithm |
| title_sort | empty nest power user identification method based on weighted random forest algorithm |
| topic | empty-nest user identification weighted random forest algorithm user electricity characteristic library data imbalance |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020249/ |
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