Bayesian Parameter Estimation of Weibull Mixtures Using Cuckoo Search

被引：3

作者：

Chi, Kuo ^{[1
]}

Kang, Jianshe ^{[1
]}

Wu, Kun ^{[1
]}

Wang, Xuan ^{[2
]}

机构：

[1] Mech Engn Coll, Dept Equipment Command & Management, Shijiazhuang, Peoples R China

[2] China Armed Police Force, Dept Elect Technol, Engn Univ, Xian, Peoples R China

来源：

2016 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT NETWORKING AND COLLABORATIVE SYSTEMS (INCOS) | 2016年

关键词：

life distribution; parameter estimation; Bayes' theorem; cuckoo search; Weibull mixtures; ALGORITHM;

D O I：

10.1109/INCoS.2016.68

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

It is difficult to estimate the parameters of Weibull mixtures precisely when using these distributions to analyze the reliability of equipment parts. As to this problem, an optimization model of the Weibull mixtures based on the Bayes theorem is proposed, and the cuckoo search is used to solve the optimization model. An case makes the diesel injector as the object of study and the two-component Weibull distribution as the life distribution. Three algorithms including cuckoo search (CS), particle swarm optimization (PSO) and genetic algorithm (GA) are used to solve the optimization model, and their solving results are compared. The result shows that the cuckoo search is the best algorithm of the three in solution efficiency and convergence performance.

引用

页码：411 / 414

页数：4

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