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
Link To Document :
بازگشت