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Bayesian Parameter Estimation of Weibull Mixtures Using Cuckoo Search

机译:杜伯尔搜索威布尔混合物的贝叶斯参数估计

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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.
机译:在使用这些分布以分析设备部件的可靠性时,难以估计Wibull混合物的参数。关于这个问题,提出了一种基于贝叶斯定理的Weibull混合物的优化模型,并使用杜鹃搜索来解决优化模型。壳体使柴油喷射器作为研究的对象和作为生命分布的双组分Weibull分布。包括杜鹃搜索(CS),粒子群优化(PSO)和遗传算法(GA)的三种算法用于解决优化模型,并比较它们的解决结果。结果表明,杜鹃搜索是解决方案效率和收敛性能的最佳算法。

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