DocumentCode
3365193
Title
Research on the Electricity Customer Credit Evaluation Based on Fuzzy Expected Value Decision-making Method Modified by Least Squares Support Vector Machine
Author
Mian Xing
Author_Institution
Sch. of Math. & Phys., North China Electr. Power Univ., Beijing
fYear
2008
fDate
4-6 Nov. 2008
Firstpage
367
Lastpage
372
Abstract
In view of electricity customer credit evaluation lacking of precise index system and hardly quantifying subjective factors and experience factors, fuzzy expected value decision-making method modified by least squares support vector machine (LS-SVM) is presented. Firstly, electricity customer credit evaluation index system is constructed; the indices values and subjective experiences values are given in the form of triangular fuzzy numbers. Then credit expected values are resulted by fuzzy expected value decision-making method. Finally, LS-SVM based on the principle of structural risk minimization modifies the expected values. The experiment shows that the credit grades after the modification suit to the original credit grades enacted by power supply enterprises and are more practicable.
Keywords
customer services; decision making; electricity supply industry; fuzzy set theory; least squares approximations; power engineering computing; risk management; support vector machines; LS-SVM; electricity customer credit evaluation; fuzzy expected value decision-making method; least squares support vector machine; power supply enterprises; structural risk minimization; triangular fuzzy numbers; Decision making; Fuzzy systems; Least squares methods; Mathematics; Physics; Power supplies; Power system modeling; Research and development management; Risk management; Support vector machines; Fuzzy; Support Vector; evaluation;
fLanguage
English
Publisher
ieee
Conference_Titel
Risk Management & Engineering Management, 2008. ICRMEM '08. International Conference on
Conference_Location
Beijing
Print_ISBN
978-0-7695-3402-2
Type
conf
DOI
10.1109/ICRMEM.2008.109
Filename
4673257
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