• Journal of Computing Science and Engineering
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• 제2권2호
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• pp.200-219
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• 2008

The effective management of uncertainty is one of the most fundamental problems in medical decision making. According to the literatures review, most medical decision models rely on point estimates for input parameters. However, it is natural that they should be interested in the relationship between changes in those values and subsequent changes in model output. Therefore, the purpose of this study is to identify the ranges of numerical values for which each option will be most efficient with respect to the input parameters. The Nonhomogeneous Poisson Process(NHPP) was used for describing the behavior of aging chronic diseases. Three kind of failure models (linear, exponential, and power law) were considered, and each of these failure models was studied under the assumptions of unknown scale factor and known aging rate, known scale factor and unknown aging rate, and unknown scale factor and unknown aging rate, respectively. In addition, this study illustrated developed method with an analysis of data from a trial of immunotherapy in the treatment of chronic Granulomatous disease. Finally, the proposed design of Bayesian value of information analysis facilitates the effective use of the computing capability of computers and provides a systematic way to integrate the expert's opinions and the sampling information which will furnish decision makers with valuable support for quality medical decision making.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권2호
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• pp.111-118
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• 2016

Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2012년도 학술발표회
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• pp.467-467
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• 2012

As the features of recent flood are spatially concentrated, loss of life and property increase by the impact of climate change. In addition to this the public interest in water control information is increased and socially reasonable justification of water control policy is needed. It is necessary to estimate the flood risk in order to let people know the status of flood control and establish flood control policy. For accurate flood risk analysis, we should consider inter-relation between causal factors of flood damage. Hence, flood risk analysis should be applied to interdependence of the factors selected. The Bayesian networks are ideally suited to assist decision-making in situations where there is uncertainty in the data and where the variables are highly interlinked. In this research, to provide more proper water control information the flood risk analysis is performed using the Bayesian networks to handle uncertainty and dependency among 13 specific proxy variables.

• 산업경영시스템학회지
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• 제8권11호
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• pp.27-34
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• 1985

Recently the distributed lag models for time series data have been used in several quantitative analyses. But the analyses of time series which have the serial correlations in error terms and the lagged values of dependent variables violate the hypothesis of OLS method. This paper suggests that the approach technique of distributed lay model with serial correlation should be applied by the Bayesian inference to estimate the parameters. For the application of distributed lag model by Bayesian analysis, the data for monthly consumption expenditure per household by items of commodities from 1972 to 1981 are used in order to estimate the lagged coefficient of processed food and the regression coefficient of the food and beverage.

• 한국환경과학회지
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• 제28권1호
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5631-5652
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• 2019

The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.

• 대한전자공학회논문지SP
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• 제41권5호
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• pp.111-116
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• 2004

웨이블릿 영역에서 Bayesian 추정법을 이용한 잡음 제거를 위해서는 웨이블릿 계수의 prior 모델, 잡음의 확률분포, 웨이블릿 계수에 대한 분산 등의 정보가 필요하다. 잡음 제거의 일반적인 방법은 웨이블릿 계수에 대한 적절한 prior 모델을 설정하고 이에 대한 신호의 분산을 추정하는 것이다. 본 논문에서는 영역 확장 방법을 사용하여 영상의 영역에 따라 분산을 추정하기 위한 창의 크기를 결정하는 방법을 제안한다. 이웃 계수의 범위는 동질성 척도를 정의하여 가장 작은 영역부터 영역을 확장하는 방법을 사용한다. 결정된 가변 이웃 영역을 사용하여 원 신호의 분산을 결정하고 이를 이용하여 웨이블릿 영역에서 Bayesian 추정법을 사용하여 영상의 잡음을 제거한다. 실험 결과를 통하여 제안 방법이 기존의 방법보다 높은 PSNR을 나타냄을 보여 준다.

• 응용통계연구
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• 제9권1호
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• pp.203-214
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• 1996

이 글에서는, 최근 논란이 계속되고 있는 교환역설문제의 진상을 규명하고, 교환문제에서는 베이지안 의사결정이 항상 유리함을 보인다. 아울러, 교환문제를 불확실성하에서의 합리적 의사결정문제로 해석한다.

• 품질경영학회지
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• 제28권4호
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• pp.67-74
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• 2000

A Bayesian burn-in procedure is developed for imited failure populations in which defective items fail soon after they are put in operation and non-defective ones never fail during he technical life of the items. Sequential schemes guaranteeing pre-specified outgoing quality of a product are derived based on prior information on the quality of a product and accumulated failure information up to the decision point. A numerical example is also provided.

• Journal of the Korean Data and Information Science Society
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• 제12권1호
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• pp.61-69
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• 2001

본 논문은 논리문장으로 표현된 지식을 처리하는 정리증명 과정에서 증명이 완료되기 전에 잠정적 결론을 유도하는 확률추론 기법을 제시한다. 정리증명 과정 중에 베이지안 해석을 이용하여 지식을 갱신하는 방법을 제시하고, 의사결정 방법을 사용하여 시간에 민감한 사안에 대해 신속하게 대처할 것인지 아니면 고의로 미룰 것인지를 결정하는 방법을 밝힌다.