• 제목/요약/키워드: Bayesian Probability Theory

검색결과 41건 처리시간 0.029초

Risk Assessment and Decision-Making of a Listed Enterprise's L/C Settlement Based on Fuzzy Probability and Bayesian Game Theory

  • Cheng, Zhang;Huang, Nanni
    • Journal of Information Processing Systems
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    • 제16권2호
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    • pp.318-328
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    • 2020
  • Letter of Credit (L/C) is currently a very popular international settlement method frequently used in international trade processes amongst countries around the globe. Compared with other international settlement methods, however, L/C has some obvious shortcomings. Firstly, it is not easy to use due to the sophisticated processes its usage involves. Secondly, it is sometimes accompanied by a few risks and some uncertainty. Thus, highly efficient methods need to be used to assess and control these risks. To begin with, FAHP and KMV methods are used to resolve the problem of incomplete information associated with L/C and then, on this basis, Bayesian game theory is used in order to make more scientific and reasonable decisions with respect to international trade.

A BAYESIAN METHOD FOR FINDING MINIMUM GENERALIZED VARIANCE AMONG K MULTIVARIATE NORMAL POPULATIONS

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • 제32권4호
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    • pp.411-423
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    • 2003
  • In this paper we develop a method for calculating a probability that a particular generalized variance is the smallest of all the K multivariate normal generalized variances. The method gives a way of comparing K multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approach for the probability is intractable and thus a Bayesian method is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach. Necessary theory involved in the method and computation is provided.

A Bayesian Approach to Paired Comparison of Several Products of Poisson Rates

  • Kim Dae-Hwang;Kim Hea-Jung
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2004년도 학술발표논문집
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    • pp.229-236
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    • 2004
  • This article presents a multiple comparison ranking procedure for several products of the Poisson rates. A preference probability matrix that warrants the optimal comparison ranking is introduced. Using a Bayesian Monte Carlo method, we develop simulation-based procedure to estimate the matrix and obtain the optimal ranking via a row-sum scores method. Necessary theory and two illustrative examples are provided.

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A Bayesian Comparison of Two Multivariate Normal Genralized Variances

  • 김혜중
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2002년도 춘계 학술발표회 논문집
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    • pp.73-78
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    • 2002
  • In this paper we develop a method for constructing a Bayesian HPD (highest probability density) interval of a ratio of two multivariate normal generalized variances. The method gives a way of comparing two multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approaches for the interval is intractable and thus a Bayesian HPD(highest probability densith) interval is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach introduced by Chen and Shao(1999). Necessary theory involved in the method and computation is provided.

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Bayesian structural damage detection of steel towers using measured modal parameters

  • Lam, Heung-Fai;Yang, Jiahua
    • Earthquakes and Structures
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    • 제8권4호
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    • pp.935-956
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    • 2015
  • Structural Health Monitoring (SHM) of steel towers has become a hot research topic. From the literature, it is impractical and impossible to develop a "general" method that can detect all kinds of damages for all types of structures. A practical method should make use of the characteristics of the type of structures and the kind of damages. This paper reports a feasibility study on the use of measured modal parameters for the detection of damaged braces of tower structures following the Bayesian probabilistic approach. A substructure-based structural model-updating scheme, which groups different parts of the target structure systematically and is specially designed for tower structures, is developed to identify the stiffness distributions of the target structure under the undamaged and possibly damaged conditions. By comparing the identified stiffness distributions, the damage locations and the corresponding damage extents can be detected. By following the Bayesian theory, the probability model of the uncertain parameters is derived. The most probable model of the steel tower can be obtained by maximizing the probability density function (PDF) of the model parameters. Experimental case studies were employed to verify the proposed method. The contributions of this paper are not only on the proposal of the substructure-based Bayesian model updating method but also on the verification of the proposed methodology through measured data from a scale model of transmission tower under laboratory conditions.

베이지안 기법을 이용한 염해 콘크리트 구조물의 내구성 평가 (Durability Assesment for Concrete Structures Exposed to Chloride Attack Using a Bayesian Approach)

  • 정현준;지광습
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2007년도 정기 학술대회 논문집
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    • pp.589-594
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    • 2007
  • This paper is shown new method for durability assesment and design have been noticed to be very valuable has been successfully applied to predict concrete structures. This paper provides that a new approach for predicting the corrosion durability of reinforced concrete structures exposed to chloride attack. In this method, the prediction can be updated successive1y by the Bayesian theory when additional data are available. The stochastic properties of model parameters are explicitly taken into account into the model the probability of the durability limit is determined from the samples obtained from the Latin hypercube sampling technique. The new method may be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures under chloride attack environments.

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A Bayesian Approach to Finite Population Sampling Using the Concept of Pivotal Quantity

  • Hwang, Hyungtae
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.647-654
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    • 2003
  • Bayesian probability models for finite populations are considered assuming so-called the super-population. We find the posterior distribution of population mean by a new approach, using the concept of pivotal quantity for the small sample case. A large sample theory is also treated throught the concept of asymptotically pivotal quantity.

Fuzzy 개념을 이용한 RC도로교의 건전성평가 모델 개발 (Development of Integrity Assessment Model for Reinforced Concrete Highway Bridges Using Fuzzy Concept)

  • 나기현;박주원;이증빈;정철원
    • 한국구조물진단유지관리공학회 논문집
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    • 제2권2호
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    • pp.151-161
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    • 1998
  • In this study, an attempt is made to apply the concept of fuzzy-bayesian theory to the integrity assessment of RC highway bridge, and uncertainty states are represented in terms of fuzzy sets which define several linguistic variables such as "very good", "good", "average", "poor", "very poor", etc. Especially, the concept of fuzzy conditional probability aids to derive a new reliability analysis which includes the subjective assessment of engineers without introducing any additional correction factors. The fuzzy concept are also used as reliability indexes for the condition assessment based on the proposed models, the proposed fuzzy theory-based approach with the results of visual inspection and extensive field load tests are applied to the integrity assessment of a new RC highway bridge, namely, Jichok bridge.

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조건부 차이조사의 관리한계 결정: 다구찌 품질손실 개념의 응용 (Determination of Control Limits of Conditional Variance Investigation: Application of Taguchi's Quality Loss Concept)

  • 배후석;임채관
    • 품질경영학회지
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    • 제49권4호
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    • pp.467-482
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    • 2021
  • Purpose: The main theme of this study is to determine the optimal control limit of conditional variance investigation by mathematical approach. According to the determination approach of control limit presented in this study, it is possible with only one parameter to calculate the control limit necessary for budgeting control system or standard costing system, in which the limit could not be set in advance, that's why it has the advantage of high practical application. Methods: This study followed the analytical methodology in terms of the decision model of information economics, Bayesian probability theory and Taguchi's quality loss function concept. Results: The function suggested by this study is as follows; ${\delta}{\leq}\frac{3}{2}(k+1)+\frac{2}{\frac{3}{2}(k+1)+\sqrt{\{\frac{3}{2}(k+1)\}^2}+4$ Conclusion: The results of this study will be able to contribute not only in practice of variance investigation requiring in the standard costing and budgeting system, but also in all fields dealing with variance investigation differences, for example, intangible services quality control that are difficult to specify tolerances (control limit) unlike tangible product, and internal information system audits where materiality standards cannot be specified unlike external accounting audits.

인공위성 원격탐사 데이타의 분석 정확도 향상에 관한 연구 -분류과정에서의 Bayesian MIC 적용을 중심으로- (Improving Correctness in the Satellite Remote Sensing Data Analysis -Laying Stress on the Application of Bayesian MLC in the Classification Stage-)

  • 안철호;김용일
    • 한국측량학회지
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    • 제9권2호
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    • pp.81-91
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    • 1991
  • 본 연구에서는 원격탐사 수치화상 데이타의 분류단계에 가중치를 고려한 Bayesian MLC를 적용하여 그 분석 정확도를 향상시키고자 하였다. 우선, Bayesian 결정법칙을 원격탐사분야 측면에서 분석해 보고 정규확률 밀도함수를 이용하여 n차원으로 확장시켰다. 이 유도과정에서 정의되는 사천확률 항에, 평행육면체 분류결과를 가중치로 적용하여 분류를 실행하였다 그리고 최종적 분류정확도는 확률함수데이타에$x^2$분포를 가정한 임계치 처리를 하므로써 오분류확률이 높은 화소를 추출하여 그 양을 기준으로 평가하였다. 연구의 전체 처리과정에 사용한 인공위성 데이타는 LANDSAT TM(1985년 10월 21일 ; 116-34)이며 연구 대상지역은 서울시 행정구역 내이다. 가중치를 적용해 본 결과 5.21%의 분석정확도 향상을 이루었으며, 따라서 본 기법은 도시 지역과 같이 복잡한 분포특성을 가지는 지형에 효과적으로 활용될 수 있다고 생각된다.

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