• 산업경영시스템학회지
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• 제28권3호
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• pp.36-41
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• 2005

페트리 네트(Petri Nets)는 이산 사건 시스템을 모델링할 수 있는 그래픽하고, 수학적인 도구이다. 본 연구는 유연제조 시스템을 확률적인 페트리 네트(Stochastic Petri Nets)중의 하나인 임베디드 마코프 체인(Embeded Markov Chain)에 도입하고, 임베디드 마코프 체인의 방법 중에 하나인 일반화된 확률적 페트리 네트(Generalized Stochastic Perti Nets)에 적용시켰다. 그리고 결과치의 정확성을 알아내기 위하여, 페트리 네트 시뮬레이션과 아레나를 사용하여 실행하였다.

• 대한수학회지
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• 제59권2호
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• pp.279-298
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• 2022

In this paper, the existence and uniqueness for the global solution of neutral stochastic functional differential equation is investigated under the locally Lipschitz condition and the contractive condition. The implicit iterative methodology and the Lyapunov-Razumikhin theorem are used. The stability analysis for such equations is also applied. One numerical example is provided to illustrate the effectiveness of the theoretical results obtained.

• Nonlinear Functional Analysis and Applications
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• 제27권4호
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• pp.813-837
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• 2022

In this paper we consider inverse problem for a general class of nonlinear stochastic differential equations on Hilbert spaces whose generating operators (drift, diffusion and jump kernels) are unknown. We introduce a class of function spaces and put a suitable topology on such spaces and prove existence of optimal generating operators from these spaces. We present also necessary conditions of optimality including an algorithm and its convergence whereby one can construct the optimal generators (drift, diffusion and jump kernel).

• Nonlinear Functional Analysis and Applications
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• 제28권2호
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• pp.365-382
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• 2023

In this paper we prove the existence and uniqueness of solution of stochastic fractional neutral differential equations with Gaussian noise or Lévy noise by using the Picard-Lindelöf successive approximation scheme. Further stability results of nonlinear stochastic fractional dynamical system with Gaussian and Lévy noises are established. Examples are provided to illustrate the theoretical results.

• 한국지반공학회지:지반
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• 제4권3호
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• pp.19-26
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• 1988

본 논문에서는 기초지반의 부등침하를 해석하기 위하여 추계론적 수치해석 방법을 사용하였다. 부등침하는 토질탄성계수의 공간적 변화와 밀접한 관계를 갖고 있다. Kriging 이론은 탄성계수의 공간적 변화를 설명하기 위하여 사용되었다. 이 방법은 선형최적불편추정기법으로 제한된 자료로 부터 최소의 분산을 가진 추정값을 구할 수 있다. 추계론적 유한요소법을 이용하여 일차근사 2차모멘트 기법으로 변위의 평균값과 분산값 그리고 공분산값을 구한다. 최종적으로 부등침하의 신뢰도모델이 제시되었다. 해석결과 두 기초사이의 거리와 탄성계수의 수평방향 변동거리가 거의 같을 때 최대부 등침하량이 일어난다는 것과 이 때 부등침하량이 허용간을 넋을 확률이 상당히 크다는 것이 밝혀 졌다.

• Structural Engineering and Mechanics
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• 제28권4호
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• pp.373-386
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• 2008

In this study stochastic analysis of non-linear dynamical systems under ${\alpha}$-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of ${\alpha}$-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with ${\alpha}/2$- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function of the system under Gaussian white noise and the probability density function of the ${\alpha}/2$-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian ${\alpha}$-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.

• 한국농공학회논문집
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• 제55권3호
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• pp.75-84
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• 2013

The seepage quantity analysis of reservoir embankment is very important for assessment of embankment safety. However, the conventional analysis does not consider uncertainty of soil properties. Permeability is known that the coefficient of variation is larger than other soil properties and seepage quantity is highly dependent on the permeability of embankment. Therefore, probabilistic analysis should be carried out for seepage analysis. To designers, however, the probabilistic analysis is not an easy task. In this paper, the method that can be performed probabilistic analysis easily and efficiently through the numerical analysis based commercial program is proposed. Stochastic response surface method is used for approximate the limit state function and when estimating the coefficients, the moving least squares method is applied in order to reduce local error. The probabilistic analysis is performed by LHC-MCS through the response surface. This method was applied to two type (homogeneous, core zone) earth dams and permeability of embankment body and core are considered as random variables. As a result, seepage quantity was predicted effectively by response surface and probabilistic analysis could be successfully implemented.

• Advances in aircraft and spacecraft science
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• 제7권5호
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• pp.405-423
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• 2020

Non-linear energy sink (NES) is an emerging passive absorber able to mitigate the dynamic response of structures without any external energy supply, resonating with all the modes of the primary structure to control. However, its inherent non-linearities hinder its large-scale use and leads to complicated design procedures. For this purpose, an approximate design approach is herein proposed in a stochastic framework. Since loads are random in nature, the stochastic analysis of non-linear systems may be performed by means of computational intensive techniques such as Monte Carlo simulations (MCS). Alternatively, the Stochastic Linearisation (SL) technique has proven to be an effective tool to investigate the performance of different passive control systems under random loads. Since controlled systems are generally non-classically damped and most of SL algorithms operate recursively, the computational burden required is still large for those problems that make intensive use of SL technique, as optimal design procedures. Herein, a procedure to speed up the Stochastic Linearisation technique is proposed by avoiding or strongly reducing numerical evaluations of response statistics. The ability of the proposed procedure to effectively reduce the computational effort and to reliably design the NES is showed through an application on a well-known case study related to the vibrations mitigation of an aircraft wing.

• 한국정보통신학회논문지
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• 제19권12호
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• pp.2828-2835
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• 2015

본 논문에서는 다양한 다중화 모형과 논스톱 포워딩 기능이 네트워크 서비스의 가용도에 미치는 영향을 비교 분석한다. 다중화 모형 중 no redundancy, 2N redundancy, N-way redundancy, N-way active redundancy 모형에 대한 확률적 리워드 네트(Stochastic Reward Net, SRN) 모델을 설계하고, 각각의 모형에 대해 논스톱 포워딩 기능을 추가한 SRN 모델을 설계한다. 확률적 페트리 네트 패키지(Stochastic Petri Net Package, SPNP)를 활용하여 설계한 SRN 모델의 가용도를 구한다.

• Communications for Statistical Applications and Methods
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• 제26권2호
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• pp.205-216
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• 2019

Diagnostic tests in medical fields detect or diagnose a disease with results measured by continuous or discrete ordinal data. The performance of a diagnostic test is summarized using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The diagnostic test is considered clinically useful if the outcomes in actually-positive cases are higher than actually-negative cases and the ROC curve is concave. In this study, we apply the stochastic ordering method in a Bayesian hierarchical model to estimate the proper ROC curve and AUC when the diagnostic test results are measured in discrete ordinal data. We compare the conventional binormal model and binormal model under stochastic ordering. The simulation results and real data analysis for breast cancer indicate that the binormal model under stochastic ordering can be used to estimate the proper ROC curve with a small bias even though the sample sizes were small or the sample size of actually-negative cases varied from actually-positive cases. Therefore, it is appropriate to consider the binormal model under stochastic ordering in the presence of large differences for a sample size between actually-negative and actually-positive groups.