• Structural Engineering and Mechanics
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• v.28 no.2
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• pp.129-152
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• 2008

This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.55-60
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• 2002

We present an extension of the Wong-Zakai type approximation theorem for a multiple stochastic integral. Using a piecewise linear approximation $W^{(n)}$ of a Wiener process W, we prove that the multiple integral processes {${\int}_{0}^{t}{\cdots}{\int}_{0}^{t}f(t_{1},{\cdots},t_{m})W^{(n)}(t_{1}){\cdots}W^{(n)}(t_{m}),t{\in}[0,T]$} where f is a given symmetric function in the space $C([0,T]^{m})$, converge to the multiple Stratonovich integral of f in the uniform $L^{2}$-sense.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.287-292
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• 2005

This paper presents a rational polynomial approximation method to estimate modal parameters of wind excited structures using incomplete noisy measurements of structural responses and partial measurements of wind velocities only. A stochastic model of the excitation wind force acting on the structure is estimated from partial measurements of wind velocities. Then the transfer functions of the structure are approximated as rational polynomial functions. From the poles and zeros of the estimated rational polynomial functions, the modal parameters, such as natural frequencies, damping ratios, and mode shapes are extracted. Since the frequency characteristics of wind forces acting on structures can be assumed as a smooth Gaussian process especially around the natural frequencies of the structures according to the central limit theorem (Brillinger, 1969; Yaglom, 1987), the estimated modal parameters are robust and reliable with respect to the assumed stochastic input models. To verify the proposed method, the modal parameters of a TV transmission tower excited by gust wind are estimated. Comparison study with the results of other researchers shows the efficacy of the suggested method.

• Journal of Advanced Research in Ocean Engineering
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• v.1 no.1
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• pp.55-62
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• 2015

Floating structure such as tension leg platform, semi-submersible and spar are widely used in field of oil exploration and renewable energy system. All of these structures have the base cylinder support structure which have effective rule in overall dynamic of response. So the accurate and reliable modeling is needed for optimum design and understanding the physical background of these systems. The aim of this article is an analytical discussion on stochastic modeling of floating cylinder based support structure but an applicable one. Due to this a mathematical mass-damper-spring system of a floating cylinder of HAWAII WTG offshore wind as an applicable and innovative system is adopted to model a coupled degrees using random vibration in analytical way. A fully develop spectrum is adopted to solve the stochastic spectrum analytically by a proper approximation. Some acceptable assumption is adopted. The simplified but analytical and innovative hydrodynamic analysis of this study not only will help researcher to concentrate more physically on hydrodynamic analysis of floating structures but also can be useful for any quick, simplified and closed form analysis of a complicated problem in offshore engineering.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.1-12
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• 2017

Many stochastic processes satisfy the Markov property exactly or at least approximately. An interested property in the Markov process is the first passage time. Since the sequential analysis by Wald, the approximation of the first passage time has been studied extensively. The Statistical computing technique due to the development of high-speed computers made it possible to calculate the values of the properties close to the true ones. This article introduces an exponentially weighted moving average (EWMA) control chart as an example of the Markov process, and studied how to calculate the average run length with problematic issues that should be cautioned for correct calculation. The results derived for approximation of the first passage time in this research can be applied to any of the Markov processes. Especially the approximation of the continuous time Markov process to the discrete time Markov chain is useful for the studies of the properties of the stochastic process and makes computational approaches easy.

• Journal of the Korean Statistical Society
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• v.26 no.1
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• pp.131-146
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• 1997

In this paper the problem of measuring the stochastic dependence among sets fo random variates is considered, and attention is specifically directed to forming a single well-defined measure of the dependence among sets of normal variates. A new information theoretic measure of the dependence called dependence index (DI) is introduced and its several properties are studied. The development of DI is based on the generalization and normalization of the mutual information introduced by Kullback(1968). For data analysis, minimum cross entropy estimator of DI is suggested, and its asymptotic distribution is obtained for testing the existence of the dependence. Monte Carlo simulations demonstrate the performance of the estimator, and show that is is useful not only for evaluation of the dependence, but also for independent model testing.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.152-155
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• 1994

The presence of joint elasticity or the arm flexibility causes low damped oscillatory position error along a desired trajectory. We utilize a stochastic model for describing the fast dynamics and the approximation error. A second order shaping filter is synthesized such that its spectrum matches that of the fast dynamics. Augmenting the state vector of slow part with that of shaping filter, we obtain a nonlinear dynamics to which a Gaussian white noise is injected. This modeling approach leads us to the design of an extended Kalman filter(KEF) and a linear quadratic Gaussian(LQG) control scheme. We present the simulation results of this control method. The simulation results show us that our Kalman filtering approach is one of prospective methods in controlling the flexible arms.

• East Asian mathematical journal
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• v.33 no.3
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• pp.271-289
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• 2017

It is our purpose in this paper to introduce the concept of best random proximity pair for subsets A and B of a separable Banach space E. We prove some best random approximation and best random proximity pair theorems of certain classes of random operators, which is the stochastic verse of the deterministic results of Eldred et al. [22], Eldred et al. [18] and Eldred and Veeramani [19]. Furthermore, our results generalize and extend recent results of Okeke and Abbas [42] and Okeke and Kim [43]. Moreover, we shall apply our results to study nonlinear stochastic integral equations of the Hammerstein type.

• Publications of The Korean Astronomical Society
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• v.7 no.1
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• pp.51-61
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• 1992

The nonlinear stochastic behavior of chaotic inflation is characterized by the 'scaling' effect. Using a simple criterion for the appearance of scaling behavior in the ${\lambda}{\phi}^4$ inflation model, we show explicitly that in this limit the onset of the scaling regime does not require any special initial conditions and that it is independent of the self-coupling constant ${\lambda}$. Non-Gaussian statistics in adiabatic fluctuations are important only for super-horizon scales and the scaling regime does not lead to any significant statistical properties on currently observable scales. However, the scaling effect gives some cosmological consequences very different from what we expect in the naive diffusion approximation for quantum fluctuations. The classical (deterministic) treatment of the inflation field (essentially a quantum mechanical object.) becomes valid towards the end of inflation.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.267-277
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• 2016

This paper considers we consider the estimation of copula parameters based on residuals in stochastic regression models. We prove that a semiparametric estimator using residual empirical distributions is consistent under some conditions and apply the results to the copula-ARMA model. We provide simulation results for illustration.