基于遗传算法的维纳退化过程可靠性估计方法

IF 0.3 Q4 ECONOMICS
Mostafa Abdul-Jabbar Dawod, Entsar Arebe Fadam
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引用次数: 0

摘要

在本文中,研究人员建议使用遗传算法方法来估计维纳退化过程的参数,其中基于维纳过程来估计高效产品的可靠性,因为使用传统技术仅依赖产品的失效次数难以估计高效产品的可靠性。通过蒙特卡罗仿真验证了该方法在参数估计方面的有效性;并与极大似然估计方法进行了比较。结果表明,基于AMSE比较准则的遗传算法方法是最优的,然后根据Wiener过程的特点,采用反高斯分布对可靠性进行估计。它还应用了一个实验的实际数据,旨在确定在特定的实验条件下灯的光强的退化
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Reliability through the Wiener Degradation Process Based on the Genetic Algorithm to Estimating Parameters
      In this paper, the researcher suggested using the Genetic algorithm method to estimate the parameters of the Wiener degradation process,  where it is based on the Wiener process in order to estimate the reliability of high-efficiency products, due to the difficulty of estimating the reliability of them using traditional techniques that depend only on the failure times of products. Monte Carlo simulation has been applied for the purpose of proving the efficiency of the proposed method in estimating parameters; it was compared with the method of the maximum likelihood estimation. The results were that the Genetic algorithm method is the best based on the AMSE comparison criterion, then the reliability was estimated by an inverse Gaussian distribution according to the characteristics of the Wiener process. It was also applied based on real data taken from an experiment intended to determine the degradation in the light intensity of lamps under specific experimental conditions
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