混合威布尔参数估计的自组织映射神经网络与分析图相结合方法

Pei-Hsi Lee, C. Torng
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引用次数: 1

摘要

混合威布尔分布被广泛用于分析磨损时间。Kececioglu提出了利用威布尔概率图(Weibull probability plot, WPP)这一图形分析方法进行参数估计的方法。然而,当数据丢失失效模式信息时,该方法不容易估计参数。采用自组织映射神经网络(SOM)对故障模式进行聚类分类。我们将SOM和Kececioglu方法结合起来估计混合威布尔分布的参数。仿真研究表明,在小样本条件下,本文方法的参数估计是准确的。
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A combined self-organizing map neural network with analysis graphical approach for mixed-weibull parameter estimation
The mixed-Weibull distribution is widely used to analyze the burn-in time. Kececioglu had presented its parameter estimation method with application of Weibull probability plot (WPP) such a graphic analysis method. However his method is not easy to estimate parameters when the data loses the failure mode information. A self-organizing map neural network (SOM) is used to cluster the classification of failure mode. We combined SOM with Kececioglu¿s method to estimate the parameters of mixed-Weibull distribution. Some simulation studies are given to present the accuracy of parameter estimation of our method under small sample size.
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