DocumentCode
2124837
Title
Application of Data Mining in Arrear Risks Prediction of Power Customer
Author
Wang, Jing-min ; Wen, Yu-qian
Author_Institution
North China Electr. Power Univ., Baoding
fYear
2008
fDate
21-22 Dec. 2008
Firstpage
206
Lastpage
210
Abstract
Difficulties in collection of electric toll have affected the normal operation and development of power supply bureau seriously. So the arrear problem of power customer has become one of the focus questions that power supply bureau pays attention to. In this paper, based on information entropy theory and on data mining technology, we have proposed a new data mining approach. This approach can measure the information amount of each index which was used to predict the arrear risks of power customer. With this approach, we have got an index system that can reflect the arrear risks. And then, support vector machines (SVM) was used to predict the arrear risks. Through empirical analysis, it has shown that the proposed approach used to arrear risk prediction had higher classification accuracy. So, it is promising to arrear risks prediction of power customer.
Keywords
consumer behaviour; data mining; power engineering computing; power system management; risk management; SVM; data mining; information entropy theory; power customer; power supply bureau development; support vector machines; Costs; Data mining; Energy consumption; Information entropy; Power supplies; Power system modeling; Predictive models; Risk analysis; Support vector machine classification; Support vector machines; SVM; arrear risks; data mining; information entropy; power customer;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3488-6
Type
conf
DOI
10.1109/KAM.2008.134
Filename
4732816
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