• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.1055-1065
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• 2003

We shall propose maximum likelihood, Bayesian and generalized maximum likelihood estimation for the reliability of the two-unit hot standby system with exponential lifetime distribution that switch is perfect. Each estimation will be compared numerically in terms of various mission times, parameter values and asymptotic relative efficiency through Monte Carlo simulation.

• Structural Engineering and Mechanics
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• v.16 no.3
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• pp.317-326
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• 2003

The tension leg platform (TLP) is a moored floating offshore structure whose buoyancy is more than its weight. The mooring system, known as tethers, is vulnerable to failure due to extreme (maximum and minimum) tensions. In the present study the reliability of these tethers under maximum and minimum tension (ultimate limit state) has been studied. Von-Mises failure criteria has been adopted to define the failure of a tether against maximum tension. The minimum tension failure criteria has been assumed to meet when the tethers slack due to loss of tension. First Order Reliability method (FORM) has been adopted for reliability assessment. The reliability, in terms of reliability index, and probability of failure has been obtained for twelve sea states. The probabilities of failure so obtained for different sea states have been adopted for the calculation of annual and life time probabilities of failure.

• International Journal of Reliability and Applications
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• v.9 no.2
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• pp.167-182
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• 2008

The objective of this paper is to discuss the stochastic analysis and the statistical inference of a three-states semi-Markov reliability model. Using the maximum likelihood procedure, the parameters included in this model are estimated. Based on the assumption that the lifetime and repair time of the system are gener-alized Weibull random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is derived. Many important special cases are discussed. Finally, the obtained results are compared with those available in the literature.

• International Journal of Reliability and Applications
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• v.6 no.1
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• pp.13-29
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• 2005

This paper deals with the stochastic analysis of a three-states semi-Markov reliability model. Using both the maximum likelihood and Bayes procedures, the parameters included in this model are estimated. Next, assuming that the lifetime and repair time are generalized exponential random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is discussed. Finally, some of the obtained results are compared with those available in the literature.

• Structural Engineering and Mechanics
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• v.3 no.2
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• pp.135-144
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• 1995

Since structural systems may fail in any one of several failure modes, computation of system reliability is always difficult. A method using numerical quadrature for computing structural system reliability with either one or more than one failure mode is presented in this paper. Statistically correlated safety margin equations are transformed into a group of uncorrelated variables and the joint density function of these uncorrelated variables can be generated by using the Maximum Entropy Method. Structural system reliability is then obtained by integrating the joint density function with the transformed safety domain enclosed within a set of linear equations. The Gaussian numerical integration method is introduced in order to improve computational accuracy. This method can be used to evaluate structural system reliability for Gaussian or non-Gaussian variables with either linear or nonlinear safety boundaries. It is also valid for implicit safety margins such as computer programs. Both the theory and the examples show that this method is simple in concept and easy to implement.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1419-1425
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• 2000

When we predict of software reliability, we can't know the testing stopping time and how many faults be residues in software the (the maximum value of data) during these software testing process, therefore we assume the maximum value and the training result can be inaccuracy. In this paper, we present neural network approach for software reliability prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data.

• International Journal of Reliability and Applications
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• v.9 no.1
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• pp.31-52
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• 2008

In this paper generalized version of the geometric distribution is introduced. This distribution can be considered as a two-parameter generalization of the discrete geometric distribution. The main statistical and reliability properties of this distribution are discussed. Two methods of estimation, namely maximum likelihood method and the method of moments are used to estimate the parameters of this distribution. Simulation is utilized to calculate these estimates and to study some of their properties. Also, asymptotic confidence limits are established for the maximum likelihood estimates. Finally, the appropriateness of this new distribution for a set of real data, compared with the geometric distribution, is shown by using the likelihood ratio test and the Kolmogorove-Smirnove test.

• International Journal of Reliability and Applications
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• v.6 no.2
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• pp.117-133
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• 2005

Estimations of the parameters included in a two-component system are derived based on masked system life test data, when the probability of masking depends upon the exact cause of system failure. Also estimations of reliability for the individual components at a specified mission time are derived. Maximum likelihood and Bayes methods are used to derive these estimators. The problem is explained on a series system consisting of two independent components each of which has a Pareto distributed lifetime. Further we present numerical studies using simulation.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1203_1204
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• 2009

Korean Tilting trains have tested on conventional lines since the beginning of 2007 for evaluating its reliability. We achieved some major performance tests which are the maximum operation speed 180km/h test and the maximum curves increasing speed with tilting operation test. In order to analysis reliability data of tilting train, we have used the special data aquisition system which consists of monitor, sensors and depot computer etc. As a results of calculation, until now we realized that the reliability are getting more increasing than starting point of running test.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.2
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• pp.97-108
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• 2008

In this paper Bayes estimator of the parameter and reliability function of the zero-truncated Poisson distribution are obtained. Furthermore, recurrence relations for the estimator of the parameter are also derived. Monte Carlo simulation technique has been made for comparing the Bayes estimator and reliability function with the corresponding maximum likelihood estimator (MLE) of zero-truncated Poisson distribution.