• 한국농공학회지
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• 제38권2호
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• pp.108-122
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• 1996

This study was to introduced estimation model for optimum probabilistic rainfall intensity on hydrological area. Originally, probabilistic rainfall intensity formula have been characterized different coefficient of formula and model following watersheds. But recently in korea rainfall intensity formula does not use unionize applyment standard between administration and district. And mingle use planning formula with not assumption model. Following the number of year hydrological duration adjust areal index. But, with adjusting formula applyment was without systematic conduct. This study perceive the point as following : 1) Use method of excess probability of Iwai to calculate survey rainfall intensity value. 2) And, use method of least squares to calculate areal coefficient for a unit of 157 rain gauge station. And, use areal coefficient was introduced new probabilistic rainfall intensity formula for each rain gauge station. 3) And, use new probabilistic rainfall intensity formula to adjust a unit of fourteen duration-a unit of fifteen year probabilistic rainfall intensity. 4) The above survey value compared with adjustment value. And use three theory of error(absolute mean error, squares mean error, relative error ratio) to choice optimum probabilistic rainfall intensity formula for a unit of 157 rain gauge station.

• 대한인간공학회지
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• 제25권4호
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• pp.41-49
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• 2006

In a decision making process, the ambiguity of qualitative probabilistic expressions may result in a wrong conclusion. For this reason there had been many studies of quantifying qualitative probabilistic expressions in English-speaking countries. In this research, quantification of Korean qualitative probabilistic expressions is conducted through 4-step questionnaires. The numerical data of 78 verbal phrases were collected in the first questionnaire and classified in two categories (i.e., uncertainty and frequency). In each category, qualitative probabilistic expressions were divided into eleven groups according to the similarity of the numerical values. In the second questionnaire, subjects selected a representative expression for each group, which totaled 11. In the third questionnaire each subject was asked to rank eleven expressions from 1 to 11 with 1 indicating the highest probability. At last, subjects conducted pairwise comparisons to obtain relative weights, which are used to convert into the numerical probability scale.

• 전자공학회논문지B
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• 제28B권10호
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• pp.831-841
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• 1991

A combined model of probabilistic and MLP(multi layer perceptron) model is proposed for the pattern classification of EMG( electromyogram) signals. The MLP model has a problem of not guaranteeing the global minima of error and different quality of approximations to Bayesian probabilities. The probabilistic model is, however, closely related to the estimation error of model parameters and the fidelity of assumptions. A proper combination of these will reduce the effects of the problems and be robust to input variations. Proposed model is able to get the MAP(maximum a posteriori probability) in the probabilistic model by estimating a priori probability distribution using the MLP model adaptively. This method minimize the error probability of the probabilistic model as long as the realization of the MLP model is optimal, and this is a good combination of the probabilistic model and the MLP model for the usage of MLP model reliability. Simulation results show the benefit of the proposed model compared to use the Mlp and the probabilistic model seperately and the average calculation time fro classification is about 50ms in the case of combined motion using an IBM PC 25 MHz 386model.

• 한국지능시스템학회논문지
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• 제17권5호
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• pp.684-690
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• 2007

본 논문은 확률변수들로 이루어진 클러스터의 집합과 확률변수들에 대해 관찰된 데이터가 주어진 상황에서, 클러스터 사이에 존재하는 조건부 확률적 의존의 방향성(directional tendency of conditional dependence in the Bayesian probabilistic graphical model)을 결정하는 방법을 기술한다. 클러스터 사이에 존재하는 조건부 확률적 의존의 방향성을 추정하기 위해 한 클러스터에서 다른 각 클러스터에 가장 가까운 확률변수를 해당 클러스터의 외부연결변수로 결정한다. 외부연결변수들 사이에서의 가장 확률이 높은 조건부 확률적 의존성을 나타내는 방향성 비순환 그래프(directed acyclic graph(DAG))를 찾음으로써, 주어진 클러스터들 사이에 존재하는 조건부 확률적 의존의 방향성을 결정한다. 사용된 방법이 클러스터 사이에 존재하는 조건부 확률적 의존의 방향성을 유의미하게 추정할 수 있음을 실험적으로 보인다.

• 한국환경보건학회지
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• 제48권5호
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• pp.266-271
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• 2022

Background: The selection of distributions of input parameters is an important component in probabilistic exposure assessment. Goodness-of-fit (GOF) methods are used to determine the distribution of exposure factors. However, there are no clear guidelines for choosing an appropriate GOF method. Objectives: The outcomes of probabilistic consumer exposure assessment were compared by using five different GOF methods for the selection of input distributions: chi-squared test, Kolmogorov-Smirnov test (K-S), Anderson-Darling test (A-D), Akaike information criterion (AIC) and Bayesian information criterion (BIC). Methods: Individual exposures were estimated based on product usage factor combinations from 10,000 respondents. The distribution of individual exposure was considered as the true value of population exposures. Results: Among the five GOF methods, probabilistic exposure distributions using the A-D and K-S methods were similar to individual exposure estimations. Comparing the 95th percentiles of the probabilistic distributions and the individual estimations for 10 CPs, there were 0.73 to 1.92 times differences for the A-D method, and 0.73 to 1.60 times differences (excluding tire-shine spray) for the K-S method. Conclusions: There were significant differences in exposure assessment results among the selection of the GOF methods. Therefore, the GOF methods for probabilistic consumer exposure assessment should be carefully selected.

• 한국농공학회지
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• 제32권E호
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• pp.59-66
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• 1990

Abstract The formulation of the probabilistic finite element method was briefly reviewed. The method was implemented into a computer program for frame analysis which has the same analogy as finite element analysis. Another program for Monte Carlo simulation of finite element analysis was written. Two sample structures were assumed and analized. The characteristics of the second moment statistics obtained by the probabilistic finite element method was examined through numerical studies. The applicability and limitation of the method were also evaluated in comparison with the data generated by Monte Carlo simulation.

• Journal of applied mathematics & informatics
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• 제4권1호
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• pp.211-222
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• 1997

In this paper we present a probabilistic approach for the estimation of realistic error bounds appearing in the execution of basic algebraic floating point operations. Experimental results are carried out for the extended product the extended sum the inner product of random normalised numbers the product of random normalised ma-trices and the solution of lower triangular systems The ordinary and probabilistic bounds are calculated for all the above processes and gen-erally in all the executed examples the probabilistic bounds are much more realistic.

• 한국지반환경공학회 논문집
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• 제10권7호
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• pp.111-115
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• 2009

국내에서는 지반의 설계응답스펙럼을 확률론적으로 생성한 지진재해도와 결정론적으로 유도된 지진계수를적용하여 생성한다. 지진재해도와 지진계수는 호환되지 않지만, 현 설계기준은 이런 근본적인 비호환성을 무시하고 있다. 지진재해도와 지진계수를 동일한 확률론적 기반에서 생성한다면 이와 같은 문제를 극복할 수 있지만, 기존의 방법으로는 지진계수를 확률론적으로 생성할 수 없다. 본 논문에서는 동반논문에서 신(新) PSHA의 결과물로써 생성된 지진기록을 입력지진파로 활용하여 1차원 등가선형 지반응답 해석을 수행하였으며 이의 결과를 기반으로 등재해스펙트럼을 생성하였다. 등재해스펙트럼의 또 한가지 장점은 지반물성치의 불확실성과 임의성이 과학적으로 고려되었다는 점이다. 등재해스펙트럼은 나아가 확률론적인 지진계수를 도출하는데 활용되었다. 확률론적인 지진계수를 내진설계기준에서 제시된 지진계수를 비교한 결과, 확률론적으로 계산된 지진계수는 결정론적으로 계산된 결과와 상당한 차이가 있는 것으로 나타났다.

• 한국지진공학회논문집
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• 제8권6호통권40호
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• pp.23-29
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• 2004

원전 구조물 및 기기의 내진설계를 위한 설계지진의 설정에는 결정론적 방법이나 확률론적 방법이 사용되어 왔다. 최근에는 확률론적 지진재해도 분석이 일반화 되면서 확률론적으로 설계지진 및 평가용 지진의 설정 방법이 합리적인 방법으로서 인식되어 많이 사용되고 있다. 우리나라의 경우 원전부지에 대한 확률론적 지진재해도 분석이 확률론적 지진위험도 평가의 일환으로 대부분 완료되어 있다. 본 연구에서는 확률론적 지진재해도의 재분해를 통하여 확률론적 시나리오 지진을 산정할 수 있는 기법을 확립하고 국내 원전 부지에 대한 확률론적 지진재해도 분석 결과를 이용하여 계산 예를 수행하였다. 이 기법을 사용하면 내진설계 및 내진안전성 평가에 활용할 수 있는 확률론적 시나리오 지진을 설정할 수 있어 매우 유용한 것으로 판단되며 합리적인 시나리오 지진의 산정을 위해서는 합리적인 지진구역도 및 감쇄식의 개발이 필요하다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.82.1-82
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• 2002

$\textbullet$ Nearest neighbor filter $\textbullet$ Probabilistic nearest neighbor filter $\textbullet$ Probabilistic nearest neighbor filter incorporating numbers of validated measurements $\textbullet$ Probability density function of the NDS $\textbullet$ Simulation results in a clutter environment to verify the performances $\textbullet$ Sensitivity analysis for the unknown spatial clutter density