Research on the Electricity Customer Credit Evaluation Based on Fuzzy Expected Value Decision-making Method Modified by Least Squares Support Vector Machine

Mian Xing
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引用次数: 1

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.
基于最小二乘支持向量机修正模糊期望值决策方法的电力客户信用评价研究
针对电力客户信用评价缺乏精确的指标体系,主观因素和经验因素难以量化的问题,提出了基于最小二乘支持向量机的模糊期望值决策方法。首先,构建了电力客户信用评价指标体系;指标值和主观经验值以三角模糊数的形式给出。然后采用模糊期望值决策方法计算出信用期望值。最后,基于结构风险最小化原则的LS-SVM对期望值进行修正。实验表明,修改后的信用等级与供电企业制定的原有信用等级相适应,更具实用性。
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