It is hard for the existing methods to obtain the expression of the system reliability for most of the practical complex systems with a large number of components and possible stales. A new regression algorithm based ...It is hard for the existing methods to obtain the expression of the system reliability for most of the practical complex systems with a large number of components and possible stales. A new regression algorithm based on the lower and upper bounds is presented in this paper, which can obtain the system reliability analytically without concerning the structure of the complex system. The method has been applied to a real system and the reliability results are compared with those acquired by the classical method and the parametric method. The effectiveness and accuracy of the proposed method have been testified.展开更多
In this paper, we discuss the mixture model of two extreme lower bound distributions. First, some properties we obtain of the model with hazard function are discussed. In addition, the estimates of the unknown paramet...In this paper, we discuss the mixture model of two extreme lower bound distributions. First, some properties we obtain of the model with hazard function are discussed. In addition, the estimates of the unknown parameters via the EM algorithm are obtained. The performance of the findings in the paper is showed by demonstrating some numerical illustrations through Monte Carlo simulation.展开更多
Stress-strength model is a basic and important tool for reliability analysis.There are few methods to assess the confidence limit of interference reliability when the distribution parameters of stress and strength are...Stress-strength model is a basic and important tool for reliability analysis.There are few methods to assess the confidence limit of interference reliability when the distribution parameters of stress and strength are all unknown.A new assessment method of interference reliability is proposed and the estimates of the distribution parameters are accordingly given.The lower confidence limit of interference reliability with given confidence can be obtained with the method even though the parameters are all unknown.Simulation studies and an engineering application are conducted to validate the method,which suggest that the method provides precise estimates even for sample size of approximately.展开更多
基金National Natural Science Foundation of China(No.40927001)
文摘It is hard for the existing methods to obtain the expression of the system reliability for most of the practical complex systems with a large number of components and possible stales. A new regression algorithm based on the lower and upper bounds is presented in this paper, which can obtain the system reliability analytically without concerning the structure of the complex system. The method has been applied to a real system and the reliability results are compared with those acquired by the classical method and the parametric method. The effectiveness and accuracy of the proposed method have been testified.
文摘In this paper, we discuss the mixture model of two extreme lower bound distributions. First, some properties we obtain of the model with hazard function are discussed. In addition, the estimates of the unknown parameters via the EM algorithm are obtained. The performance of the findings in the paper is showed by demonstrating some numerical illustrations through Monte Carlo simulation.
文摘Stress-strength model is a basic and important tool for reliability analysis.There are few methods to assess the confidence limit of interference reliability when the distribution parameters of stress and strength are all unknown.A new assessment method of interference reliability is proposed and the estimates of the distribution parameters are accordingly given.The lower confidence limit of interference reliability with given confidence can be obtained with the method even though the parameters are all unknown.Simulation studies and an engineering application are conducted to validate the method,which suggest that the method provides precise estimates even for sample size of approximately.
