• 제목/요약/키워드: Stochastic order

검색결과 581건 처리시간 0.021초

Vibration and stability of fluid conveying pipes with stochastic parameters

  • Ganesan, R.;Ramu, S. Anantha
    • Structural Engineering and Mechanics
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    • 제3권4호
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    • pp.313-324
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    • 1995
  • Flexible cantilever pipes conveying fluids with high velocity are analysed for their dynamic response and stability behaviour. The Young's modulus and mass per unit length of the pipe material have a stochastic distribution. The stochastic fields, that model the fluctuations of Young's modulus and mass density are characterized through their respective means, variances and autocorrelation functions or their equivalent power spectral density functions. The stochastic non self-adjoint partial differential equation is solved for the moments of characteristic values, by treating the point fluctuations to be stochastic perturbations. The second-order statistics of vibration frequencies and mode shapes are obtained. The critical flow velocity is first evaluated using the averaged eigenvalue equation. Through the eigenvalue equation, the statistics of vibration frequencies are transformed to yield critical flow velocity statistics. Expressions for the bounds of eigenvalues are obtained, which in turn yield the corresponding bounds for critical flow velocities.

구간 자료의 확률적 순서 검정 (Testing for stochastic order in interval-valued data)

  • 최혜정;임요한;곽민정;박성오
    • 응용통계연구
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    • 제32권6호
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    • pp.879-887
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    • 2019
  • 본 연구에서는 이표본 구간 자료의 확률적 순서 검정 절차를 제안한다. 제안하는 검정 통계량은 U-통계량에 해당하며 본 연구에서는 이에 대한 점근적 분포를 귀무 가설 하에서 유도하였다. 실제 자료와 모의 실험을 통해 새로 제안한 방법의 성능을 단측 이변량 Kolmogorov-Smirnov 검정법과 비교한다.

Min-Max Stochastic Optimization with Applications to the Single-Period Inventory Control Problem

  • Park, Kyungchul
    • Management Science and Financial Engineering
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    • 제21권1호
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    • pp.11-17
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    • 2015
  • Min-max stochastic optimization is an approach to address the distribution ambiguity of the underlying random variable. We present a unified approach to the problem which utilizes the theory of convex order on the random variables. First, we consider a general framework for the problem and give a condition under which the convex order can be utilized to transform the min-max optimization problem into a simple minimization problem. Then extremal distributions are presented for some interesting classes of distributions. Finally, applications to the single-period inventory control problems are given.

Design Centering by Genetic Algorithm and Coarse Simulation

  • Jinkoo Lee
    • 한국CDE학회논문집
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    • 제2권4호
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    • pp.215-221
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    • 1997
  • A new approach in solving design centering problem is presented. Like most stochastic optimization problems, optimal design centering problems have intrinsic difficulties in multivariate intergration of probability density functions. In order to avoid to avoid those difficulties, genetic algorithm and very coarse Monte Carlo simulation are used in this research. The new algorithm performs robustly while producing improved yields. This result implies that the combination of robust optimization methods and approximated simulation schemes would give promising ways for many stochastic optimizations which are inappropriate for mathematical programming.

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THE APPLICATION OF STOCHASTIC ANALYSIS TO COUNTABLE ALLELIC DIFFUSION MODEL

  • Choi, Won
    • 대한수학회보
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    • 제41권2호
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    • pp.337-345
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    • 2004
  • In allelic model X = ($\chi_1\chi$_2ㆍㆍㆍ, \chi_d$), M_f(t) = f(p(t)) - ${{\int^t}_0}\;Lf(p(t))ds$ is a P-martingale for diffusion operator L under the certain conditions. In this note, we can show existence and uniqueness of solution for stochastic differential equation and martingale problem associated with mean vector. Also, we examine that if the operator related to this martingale problem is connected with Markov processes under certain circumstance, then this operator must satisfy the maximum principle.

Control of an stochastic nonlinear system by the method of dynamic programming

  • Choi, Wan-Sik
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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    • pp.156-161
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    • 1994
  • In this paper, we consider an optimal control problem of a nonlinear stochastic system. Dynamic programming approach is employed for the formulation of a stochastic optimal control problem. As an optimality condition, dynamic programming equation so called the Bellman equation is obtained, which seldom yields an analytical solution, even very difficult to solve numerically. We obtain the numerical solution of the Bellman equation using an algorithm based on the finite difference approximation and the contraction mapping method. Optimal controls are constructed through the solution process of the Bellman equation. We also construct a test case in order to investigate the actual performance of the algorithm.

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AN APPROXIMATED EUROPEAN OPTION PRICE UNDER STOCHASTIC ELASTICITY OF VARIANCE USING MELLIN TRANSFORMS

  • Kim, So-Yeun;Yoon, Ji-Hun
    • East Asian mathematical journal
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    • 제34권3호
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    • pp.239-248
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    • 2018
  • In this paper, we derive a closed-form formula of a second-order approximation for a European corrected option price under stochastic elasticity of variance model mentioned in Kim et al. (2014) [1] [J.-H. Kim, J Lee, S.-P. Zhu, S.-H. Yu, A multiscale correction to the Black-Scholes formula, Appl. Stoch. Model. Bus. 30 (2014)]. To find the explicit-form correction to the option price, we use Mellin transform approaches.

Single Machine Sequencing With Random Processing Times and Random Deferral Costs

  • Park, Sung H.
    • 한국경영과학회지
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    • 제4권1호
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    • pp.69-77
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    • 1979
  • A single machine stochastic scheduling problem is considered. Associated with each job is its random processing time and random deferral cost. The criterion is to order the jobs so as to minimize the sum of the deferral costs. The expected sum of the deferral costs is theroretically derived under the stochastic situation for each of several scheduling decision rules which are well known for the deterministic environment. It is also shown that certain stochastic problems can be reduced to equivalent deterministic problems. Two examples are illustrated to show the expected total deferral costs.

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PERMANENTS OF DOUBLY STOCHASTIC FERRERS MATRICES

  • Hwang, Suk-Geun;Pyo, Sung-Soo
    • 대한수학회지
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    • 제36권5호
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    • pp.1009-1020
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    • 1999
  • The minimum permanent and the set of minimizing matrices over the face of the polytope n of all doubly stochastic matrices of order n determined by any staircase matrix was determined in [4] in terms of some parameter called frame. A staircase matrix can be described very simply as a Ferrers matrix by its row sum vector. In this paper, some simple exposition of the permanent minimization problem over the faces determined by Ferrers matrices of the polytope of n are presented in terms of row sum vectors along with simple proofs.

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A Note on Estimation Under Discrete Time Observations in the Simple Stochastic Epidemic Model

  • Oh, Chang-Hyuck
    • Journal of the Korean Statistical Society
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    • 제22권1호
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    • pp.133-138
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    • 1993
  • We consider two estimators of the infection rate in the simple stochastic epidemic model. It is shown that the maximum likelihood estimator of teh infection rate under the discrete time observation does not have the moment of any positive order. Some properties of the Choi-Severo estimator, an approximation to the maximum likelihood estimator, are also investigated.

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