• 제목/요약/키워드: Stochastic Distribution

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Seismic response distribution estimation for isolated structures using stochastic response database

  • Eem, Seung-Hyun;Jung, Hyung-Jo
    • Earthquakes and Structures
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    • 제9권5호
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    • pp.937-956
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    • 2015
  • Seismic isolation systems decouple structures from ground motions to protect them from seismic events. Seismic isolation devices have been implemented in many full-scale buildings and bridges because of their simplicity, economic effectiveness, inherent stability, and reliability. It is well known that the most uncertain aspect for obtaining the accurate responses of an isolated structure from seismic events is the seismic loading itself. It is needed to know the seismic response distributions of the isolated structure resulting from the randomness of earthquakes when probabilistic designing or probabilistic evaluating an isolated structure. Earthquake time histories are useful and often an essential element for designing or evaluating isolated structures. However, it is very challenging to gather the design and evaluation information for an isolated structure from many seismic analyses. In order to evaluate the seismic performance of an isolated structure, numerous nonlinear dynamic analyses need to be performed, but this is impractical. In this paper, the concept of the stochastic response database (SRD) is defined to obtain the seismic response distributions of an isolated structure instantaneously, thereby significantly reducing the computational efforts. An equivalent model of the isolated structure is also developed to improve the applicability and practicality of the SRD. The effectiveness of the proposed methodology is numerically verified.

베이지언 추론에 기반한 확률론적 피로수명 평가 (Stochastic Fatigue Life Assesment based on Bayesian-inference)

  • 박명진;김유일
    • 대한조선학회논문집
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    • 제56권2호
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    • pp.161-167
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    • 2019
  • In general, fatigue analysis is performed by using deterministic model to estimate the optimal parameters. However, the deterministic model is difficult to clearly describe the physical phenomena of fatigue failure that contains many uncertainty factors. With regard to this, efforts have been made in this research to compare with the deterministic model and the stochastic models. Firstly, One deterministic S-N curve was derived from ordinary least squares technique and two P-S-N curves were estimated through Bayesian-linear regression model and Markov-Chain Monte Carlo simulation. Secondly, the distribution of Long-term fatigue damage and fatigue life were predicted by using the parameters obtained from the three methodologies and the long-term stress distribution.

Application of GTH-like algorithm to Markov modulated Brownian motion with jumps

  • Hong, Sung-Chul;Ahn, Soohan
    • Communications for Statistical Applications and Methods
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    • 제28권5호
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    • pp.477-491
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    • 2021
  • The Markov modulated Brownian motion is a substantial generalization of the classical Brownian Motion. On the other hand, the Markovian arrival process (MAP) is a point process whose family is dense for any stochastic point process and is used to approximate complex stochastic counting processes. In this paper, we consider a superposition of the Markov modulated Brownian motion (MMBM) and the Markovian arrival process of jumps which are distributed as the bilateral ph-type distribution, the class of which is also dense in the space of distribution functions defined on the whole real line. In the model, we assume that the inter-arrival times of the MAP depend on the underlying Markov process of the MMBM. One of the subjects of this paper is introducing how to obtain the first passage probabilities of the superposed process using a stochastic doubling algorithm designed for getting the minimal solution of a nonsymmetric algebraic Riccatti equation. The other is to provide eigenvalue and eigenvector results on the superposed process to make it possible to apply the GTH-like algorithm, which improves the accuracy of the doubling algorithm.

ESTIMATING THE LOSS RATIO OF SOLAR PHOTOVOLTAIC ELECTRICITY GENERATION THROUGH STOCHASTIC ANALYSIS

  • Taehoon Hong;Choongwan Koo;Minhyun Lee
    • 국제학술발표논문집
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    • The 5th International Conference on Construction Engineering and Project Management
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    • pp.375-385
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    • 2013
  • As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

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시뮬레이션과 수리모델을 이용한 생산-분배 계획 (A HYBRID SIMULATION- ANALYTIC METHOD FOR PRODUCTION-DISTRIBUTION PLANNING)

  • 김숙한;이영해
    • 한국시뮬레이션학회:학술대회논문집
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    • 한국시뮬레이션학회 2000년도 춘계학술대회 논문집
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    • pp.57-66
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    • 2000
  • Production-distribution planning is the most important part in supply chain management (SCM). To solve this planning problem, either analytic or simulation approach has been developed. However these two approaches have their own demerits in problem solving. In this paper, we propose a hybrid approach which is a specific problem solving procedure combining analytic and simulation method to solve production-distribution problems in supply chain. The machine capacity and distribution capacity constraints in the analytic model are considered as stochastic factors and adjusted by the proposed specific process according to the results from independently developed simulation model which includes general production-distribution characteristics.

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확률적 최적화를 활용한 연속적인 공극비 기울기를 갖는 시멘트 풀 가상 시편 제작 및 투기율 분석 (Evaluation of Air Permeability of Virtual Cement Paste Specimen with Linear Void Ratio Gradient Constructed using Stochastic Optimization)

  • 김세윤;한동석
    • 한국전산구조공학회논문집
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    • 제29권5호
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    • pp.463-469
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    • 2016
  • 본 논문에서는 저차원 확률 함수를 사용하여 연속적인 선형 공극비 기울기를 갖는 기능경사재료 형태의 가상 시편을 제작하였다. 실제 물 시멘트 비가 다른 두 종류 시멘트 풀 시편의 X-선 CT 단면 이미지를 통해 3차원 공극 분포 모델을 제작하여 이를 기반으로 가상 시편을 제작하였다. 가상 시편이 두 실제 시편 사이에 위치하도록 공극 분포 특성을 저차원 확률 함수와 공극비 기울기로 구성하였다. 공극 분포의 기울기는 연속적인 형태의 수직 방향의 선형 공극비 기울기로 구현하며, 이를 위해 확률적 최적화의 목적 함수로 저차원 확률 함수와 공극비 기울기에 관한 함수를 사용하였다. 가상 시편 내 공극 분포 특성 확인을 위해 본 연구에서는 투기율 분석을 유한요소해석을 통해 수행하였다. 공극 분포 특성과 투기율 해석 결과를 비교하여 가상 시편이 갖는 공극 분포 특성이 투기율에 미치는 영향을 확인하고, 투기율의 실제 실험 결과와 해석 결과의 비교를 통해 해석 결과의 타당성을 입증하였다.

ON OPTIMIZATION OF METAL FORMING WITH ADAPTABLE CHARACTERISTICS

  • Gitman, Michael B.;Trusov, Peter V.;Redoseev, Sergei A.
    • Journal of applied mathematics & informatics
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    • 제7권2호
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    • pp.507-516
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    • 2000
  • In the present paper we consider a problem of choosing the rational way to carry on the metal processing (the problem of stochastic optimization) and the problem of determing the unknown characteristics of parameters described with random variables.

Behrens-Fisher Problem from a Model Selection Point of View

  • Jeon, Jong-Woo;Lee, Kee-Won
    • Journal of the Korean Statistical Society
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    • 제20권2호
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    • pp.99-107
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    • 1991
  • Behrens-Fisher problem is viewed from a model selection approach. Normal distribution is regarded as an approximating model, A criterion, called TIC, is derived and is compared with selection criteria such as AIC and a bootstrap estimator. Stochastic approximation is used since no closed form expression is available for the bootstrap estimator.

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Lagged Unstable Regressor Models and Asymptotic Efficiency of the Ordinary Least Squares Estimator

  • Shin, Dong-Wan;Oh, Man-Suk
    • Journal of the Korean Statistical Society
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    • 제31권2호
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    • pp.251-259
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    • 2002
  • Lagged regressor models with general stationary errors independent of the regressors are considered. The regressor process is unstable having characteristic roots on the unit circle. If the order of the lag matches the number of roots on the unit circle, the ordinary least squares estimator (OLSE) is asymptotically efficient in that it has the same limiting distribution as the generalized least squares estimator (GLSE) under the same normalization. This result extends the well-known result of Grenander and Rosenblatt (1957) for asymptotic efficiency of the OLSE in deterministic polynomial and/or trigonometric regressor models to a class of models with stochastic regressors.

확률모형에 등장하는 최대와 최소의 특성에 관한 소고 (On the Characteristics of Maximum and Minimum of Random Variables in Stochastic Models)

  • 채경철;김진동;양원석
    • 한국경영과학회지
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    • 제26권4호
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    • pp.39-45
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    • 2001
  • Maximum and minimum of rendom variables are frequently encountered in the stochastic modelling for various OR problems. We summarize and extend characteristics of maximum and minimum, emphasizing the case in which random variables are independent and all of them except one are distributed exponential. As an application, we derive a transform-free expression for the M/G/1 queue length distribution.

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