M-FSVM在可靠性寿命分布模式识别中的应用CSCD

在产品的可靠性研究中,准确、有效地识别产品所属的寿命分布,是可靠性建模成败的关键。针对传统支持向量机(SVM)在解决多分类问题时存在不可分区域等缺陷,提出了一种基于多分类模糊支持向量机(M-FSVM)的可靠性寿命分布模式识别方法,建立了包括指数分布、正态分布、对数正态分布和威布尔分布四种常用寿命分布模式识别的模糊支持向量机模型,并进行了仿真试验研究。仿真试验结果表明,该模型能够克服传统支持向量机中存在的不足,能够对常用的寿命分布模式进行智能识别,识别率高,便于工程应用。

Identification of Reliability Life Distribution with Multi-class Fuzzy Support Vector Machine

In the field of product reliability study, identifying the reliability life distribution of a product accurately and efficiently is a key to the result of reliability modeling. The traditional Support Vector Machine (SVM) has some defects, such as unclassifiable region in multiclass classification. Aiming at those defects, a method of identifying the reliability life distribution with Multi-class Fuzzy Support Vector Machine(M-FSVM) is proposed, establishing four common models of reliability life distribution including exponential distribution, normal distribution, lognormal distribution and Weibull distribution, and is confirmed by simulation. The results show that, this method can overcome the shortcomings of traditional SVM, identify common life distribution intelligently with high recognition rate, and is convenient for the engineering application.