• Communications for Statistical Applications and Methods
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• v.27 no.4
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• pp.469-486
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• 2020

Entropy is an important term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we consider the maximum likelihood estimation (MLE), maximum product spacings estimation (MPSE) and Bayesian estimation of the entropy of an inverse Weibull distribution (InW) under a generalized type I progressive hybrid censoring scheme (GePH). The MLE and MPSE of the entropy cannot be obtained in closed form; therefore, we propose using the Newton-Raphson algorithm to solve it. Further, the Bayesian estimators for the entropy of InW based on squared error loss function (SqL), precautionary loss function (PrL), general entropy loss function (GeL) and linex loss function (LiL) are derived. In addition, we derive the Lindley's approximate method (LiA) of the Bayesian estimates. Monte Carlo simulations are conducted to compare the results among MLE, MPSE, and Bayesian estimators. A real data set based on the GePH is also analyzed for illustrative purposes.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.1
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• pp.37-50
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• 2000

We are concerned with estimating the average performance of a re-entrant line with single-job machines and batch machines. The system has multiclass jobs, which will be processed in predetermined routes. An analytical approach may be intractable since the system would not be modeled by product form queueing networks due to the inclusion of batch machines and the consideraton of multiclass jobs which have different processing times. We propose an approximation method based on the Mean Value Analysis(MVA). Our method obtains the mean walting time in each buffer of a workstation and the mean cycle time using the MVA and heuristics. numerical experiments show that the errors of our method are within 5% compared with simulation.

• Journal of computational fluids engineering
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• v.11 no.1 s.32
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• pp.21-28
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• 2006

Reliability Based Design Optimization(RBDO) is one of the optimization methods that minimize the product failure due to small changes of operating conditions or process errors. It searches the optimum that satisfies the safety margin of each constraint, and it gives stable and reliable designs. However, RBDO requires many times oj computational efforts compared with the conventional deterministic optimization(DO) to evaluate the probability of failure about each constraint, therefore it is hard to apply directly to large-scaled problems such as a flexible wing shape design optimization. For the efficient reliability analysis, the approximate reliability analysis method with the two-point approximation(TPA) is proposed In this study, the lift-to-drag ratio maximization designs are performed with 3-dimensional Navier-Stokes analysis and NASTRAN structural analysis, and the optimization results about the deterministic, FORM and SORM are compared.

• Structural Engineering and Mechanics
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• v.38 no.6
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• pp.733-751
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• 2011

In the present study, a new kind of multivariable Reissner-Mindlin plate elements with two kinds of variables based on B-spline wavelet on the interval (BSWI) is constructed to solve the static and vibration problems of a square Reissner-Mindlin plate, a skew Reissner-Mindlin plate, and a Reissner-Mindlin plate on an elastic foundation. Based on generalized variational principle, finite element formulations are derived from generalized potential energy functional. The two-dimensional tensor product BSWI is employed to form the shape functions and construct multivariable BSWI elements. The multivariable wavelet finite element method proposed here can improve the solving accuracy apparently because generalized stress and strain are interpolated separately. In addition, compared with commonly used Daubechies wavelet finite element method, BSWI has explicit expression and a very good approximation property which guarantee the satisfying results. The efficiency of the proposed multivariable Reissner-Mindlin plate elements are verified through some numerical examples in the end.