• 한국농공학회논문집
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• 제56권1호
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• pp.11-20
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• 2014

Many classification studies for the community of densely-connected nodes are limited to the comprehensive analysis for detecting the communities in probabilistic networks with nodes and edge of the probabilistic distribution because of the difficulties of the probabilistic operation. This study aims to use convolution method for operating nodes and edge of probabilistic distribution. For the probabilistic hierarchy network with nodes and edges of the probabilistic distribution, the model of this study detects the communities of nodes to make the new probabilistic distribution with two distribution. The results of our model was verified through comparing with Monte-carlo Simulation and other community-detecting methods.

• 한국지반공학회논문집
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• 제25권11호
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• pp.87-103
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• 2009

지반정수의 신뢰성 높은 확률분포형을 결정하기 위해서는 분석자료에 대한 이상치 및 무작위성 검정, 적용한 확률 분포형의 매개변수 추정 및 매개변수 적합성 검정, 마지막으로 확률분포형의 적합성 검정의 과정이 필요하며, 위의 순서로 지반정수의 확률분포형을 산정할 것을 제안하였다. 본 연구에서는 제안한 절차에 따라 분석대상 지반으로 선정된 인천 송도지역 지반정수들의 확률분포형을 추정하였으며, 추가로 지반정수들의 변동성을 나타내는 변동계수를 산정하였다. 이와 같이 신뢰성 높은 지반정수들의 확률분포형과 변동계수는 확률론적 설계방법에 사용될 수 있을 뿐만 아니라 결정론적 설계에 사용될 지반정수의 합리적인 결정에 사용될 수 있는 중요한 자료로 판단된다.

• 대한안전경영과학회지
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• 제2권2호
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• pp.71-83
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• 2000

This paper presents accelerated life tests for Type I censoring data under probabilistic stresses. Probabilistic stress, $S_j$, is the random variable for stress influenced by test environments, test equipments, sampling devices and use conditions. The hazard rate, ,$theta_j$, is the random variable of environments and the function of probabilistic stress. Also it is assumed that the general stress distribution is uniform, the life distribution for the given hazard rate, $\theta$, is exponential and inverse power law model holds. In this paper, we obtained maximum likelihood estimators of model parameters and the mean life in use stress condition.

• 한국농공학회지
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• 제36권3호
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• pp.122-134
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• 1994

The objective of this study is to provide with the hydrometeological and probabilistic characteristics of the storms and winds of typhoons that have been passed through the Korea peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall and wind data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. Wind data were also analysed for their probabilistic distributions. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that have passed through the Korean peninsula was type E, which was followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, that was followed by A, super A, and C types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution for typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution. 5. The most frequent probabilistic distribution for typhoon wind events was Type-I xtremal distribution, followed by Two-parameter lognormal distribution, and Normal distribution.

• 대한전기학회논문지:전력기술부문A
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• 제55권3호
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• pp.109-115
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• 2006

The Weibull distribution is a good candidate for accurate probabilistic model with its rich shape-forming ability and relatively simple CDF(cumulative distribution function). If there are sufficient information to get convincible mean and variance for a probabilistic event, reliable parameters of the Weibull distribution can be determined uniquely. However, sufficient information is not given as usual. There needs more deliberate model building method for that case. This Paper presents an effective parameter estimation technique for Weibull distribution with limited failure data.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.461-470
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• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• 산업경영시스템학회지
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• 제24권68호
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• pp.1-7
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• 2001

A probabilistic model for fatigue life of a structural component is derived when the component is in a variable-amplitude loading environment. The physical mechanism which governs fatigue failure is used to model the fatigue life. Especially, the judgement of rotational symmetry in the-stress-intensity-factors results in the probability distribution for fatigue life. The probability distribution is related to the familiar truncated Gaussian distribution, which has a single parameter with a direct physical meaning.

• 한국멀티미디어학회논문지
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• 제23권4호
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• pp.595-602
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• 2020

We propose a generative probabilistic model with Dirichlet prior distribution for topic modeling and text similarity analysis. It assigns a topic and calculates text correlation between documents within a corpus. It also provides posterior probabilities that are assigned to each topic of a document based on the prior distribution in the corpus. We then present a Gibbs sampling algorithm for inference about the posterior distribution and compute text correlation among 50 abstracts from the papers published by IEEE. We also conduct a supervised learning to set a benchmark that justifies the performance of the LDA (Latent Dirichlet Allocation). The experiments show that the accuracy for topic assignment to a certain document is 76% for LDA. The results for supervised learning show the accuracy of 61%, the precision of 93% and the f1-score of 96%. A discussion for experimental results indicates a thorough justification based on probabilities, distributions, evaluation metrics and correlation coefficients with respect to topic assignment.

• 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.

• 컴퓨터교육학회논문지
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• 제6권1호
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• pp.29-39
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• 2003

이 논문에서는 웹 미디어(웹 기반의 하이퍼미디어) 시스템에서 이산 확률 분포 함수와 사용자 프로파일 기반의 동적 적응 모델을 제안하였다. 이 모델은 응용 영역을 동적 적응 객체의 가중치 방향성 그래프로 표현하며, 사용자 행위를 이산 확률 함수를 동적으로 구축하는 접근 방식을 이용하여 모델링한다. 제안한 확률적 해석은 웹 미디어 구조에서 사용자의 탐색 행위를 추적하여 사용자 행위에 대한 잠재적 속성을 나타내는데 사용될 수 있다. 이러한 접근 방식은 사용자에게 가장 알맞은 프로파일을 동적으로 할당할 수 있다.