• Title/Summary/Keyword: 확률 모형

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Development of Probability Theory based Dynamic Travel Time Models (확률론적 이론에 기초한 동적 통행시간 모형 정립)

  • Yang, Chul-Su
    • Journal of Korean Society of Transportation
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    • v.29 no.3
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    • pp.83-91
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    • 2011
  • This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.

A Study on the Computational Model of Word Sense Disambiguation, based on Corpora and Experiments on Native Speaker's Intuition (직관 실험 및 코퍼스를 바탕으로 한 의미 중의성 해소 계산 모형 연구)

  • Kim, Dong-Sung;Choe, Jae-Woong
    • Korean Journal of Cognitive Science
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    • v.17 no.4
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    • pp.303-321
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    • 2006
  • According to Harris'(1966) distributional hypothesis, understanding the meaning of a word is thought to be dependent on its context. Under this hypothesis about human language ability, this paper proposes a computational model for native speaker's language processing mechanism concerning word sense disambiguation, based on two sets of experiments. Among the three computational models discussed in this paper, namely, the logic model, the probabilistic model, and the probabilistic inference model, the experiment shows that the logic model is first applied fer semantic disambiguation of the key word. Nexr, if the logic model fails to apply, then the probabilistic model becomes most relevant. The three models were also compared with the test results in terms of Pearson correlation coefficient value. It turns out that the logic model best explains the human decision behaviour on the ambiguous words, and the probabilistic inference model tomes next. The experiment consists of two pans; one involves 30 sentences extracted from 1 million graphic-word corpus, and the result shows the agreement rate anong native speakers is at 98% in terms of word sense disambiguation. The other pm of the experiment, which was designed to exclude the logic model effect, is composed of 50 cleft sentences.

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두 가지 불완전수리모형의 최적화

  • 이의용;최승경
    • Proceedings of the Korean Reliability Society Conference
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    • 2000.04a
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    • pp.47-53
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    • 2000
  • Brown과 Proschan의 수리모형과 이를 일반화한 Lee와 Seoh의 시스템 수리모형이 고려된다. Brown과 Proschan의 수리모형은 시스템의 고장시 완전수리가 확률 p로, 불완전수리가 확률 1-p로 이루어지는 모형이고, Lee와 Seoh의 수리모형은 시스템 고장시 완전수리와 불완전수리의 선택이 마르코프 연쇄과정에 따라 결정되는 모형이다. 본 논문에서는, 완전수리비용과 불완전수리비용을 고려한 후, 시스템의 수명분포가 지수분포, 균일분포, Weibull분포인 경우로 나누어, 위 두 시스템 수리모형에서의 최적화가 연구된다.

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Solution Algorithms for Logit Stochastic User Equilibrium Assignment Model (확률적 로짓 통행배정모형의 해석 알고리듬)

  • 임용택
    • Journal of Korean Society of Transportation
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    • v.21 no.2
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    • pp.95-105
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    • 2003
  • Because the basic assumptions of deterministic user equilibrium assignment that all network users have perfect information of network condition and determine their routes without errors are known to be unrealistic, several stochastic assignment models have been proposed to relax this assumption. However. it is not easy to solve such stochastic assignment models due to the probability distribution they assume. Also. in order to avoid all path enumeration they restrict the number of feasible path set, thereby they can not preciously explain the travel behavior when the travel cost is varied in a network loading step. Another problem of the stochastic assignment models is stemmed from that they use heuristic approach in attaining optimal moving size, due to the difficulty for evaluation of their objective function. This paper presents a logit-based stochastic assignment model and its solution algorithm to cope with the problems above. We also provide a stochastic user equilibrium condition of the model. The model is based on path where all feasible paths are enumerated in advance. This kind of method needs a more computing demand for running the model compared to the link-based one. However, there are same advantages. It could describe the travel behavior more exactly, and too much computing time does not require than we expect, because we calculate the path set only one time in initial step Two numerical examples are also given in order to assess the model and to compare it with other methods.

2002년 월드컵 축구 예제를 활용한 수학 I 의 확률학습모형 개발

  • Park, Dong-Jun;Park, Gwang-Won
    • Communications of Mathematical Education
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    • v.12
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    • pp.265-280
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    • 2001
  • 고등학교 수학 I 의 확률 및 통계영역의 교육내용을 정리한 후, 고등학생들에게 확률 및 통계영역에 관한 흥미를 돋구기 위하여 2002년 월드컵을 소재로 한 문제들을 활용하여 비주얼 베이직으로 프로그램한 ‘확률상자’ 라는 확률모형을 개발하였다. 확률상자에는 확률의 역사, 경우의 수, 순열, 같은 것이 있는 순열, 원순열, 조합, 이항계수, 통계적 확률, 조건부 확률, 배반사건 등 모두 10가지 모듈을 포함한다. 확률상자의 초기화면에서 메뉴를 선택하면 선택된 내용에 관한 간단한 정의와 함께 문제가 제시되어 정답을 적도록 하였고, 오답일 때는 힌트를 누르면 정답을 이해할 수 있도록 풀이과정을 제시하였다. 특히, 메뉴가운데서 경우의 수, 순열, 같은 것이 있는 순열, 원순열, 조합, 통계적 확률의 경우에는 풀이과정 중에 애니메이션 또는 시뮬레이션이 실행되도록 하여 이해를 돕도록 하였다.

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Bayesian Variable Selection in Linear Regression Models with Inequality Constraints on the Coefficients (제한조건이 있는 선형회귀 모형에서의 베이지안 변수선택)

  • 오만숙
    • The Korean Journal of Applied Statistics
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    • v.15 no.1
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    • pp.73-84
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    • 2002
  • Linear regression models with inequality constraints on the coefficients are frequently used in economic models due to sign or order constraints on the coefficients. In this paper, we propose a Bayesian approach to selecting significant explanatory variables in linear regression models with inequality constraints on the coefficients. Bayesian variable selection requires computation of posterior probability of each candidate model. We propose a method which computes all the necessary posterior model probabilities simultaneously. In specific, we obtain posterior samples form the most general model via Gibbs sampling algorithm (Gelfand and Smith, 1990) and compute the posterior probabilities by using the samples. A real example is given to illustrate the method.

Heat-Wave Data Analysis based on the Zero-Inflated Regression Models (영-과잉 회귀모형을 활용한 폭염자료분석)

  • Kim, Seong Tae;Park, Man Sik
    • Journal of the Korean Data Analysis Society
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    • v.20 no.6
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    • pp.2829-2840
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    • 2018
  • The random variable with an arbitrary value or more is called semi-continuous variable or zero-inflated one in case that its boundary value is more frequently observed than expected. This means the boundary value is likely to be practically observed more than it should be theoretically under certain probability distribution. When the distribution considered is continuous, the variable is defined as semi-continuous and when one of discrete distribution is assumed for the variable, we regard it as zero-inflated. In this study, we introduce the two-part model, which consists of one part for modelling the binary response and the other part for modelling the variable greater than the boundary value. Especially, the zero-inflated regression models are explained by using Poisson distribution and negative binomial distribution. In real data analysis, we employ the zero-inflated regression models to estimate the number of days under extreme heat-wave circumstances during the last 10 years in South Korea. Based on the estimation results, we create prediction maps for the estimated number of days under heat-wave advisory and heat-wave warning by using the universal kriging, which is one of the spatial prediction methods.

Development of Stochastic Markov Process Model for Maintenance of Armor Units of Rubble-Mound Breakwaters (경사제 피복재의 유지관리를 위한 추계학적 Markov 확률모형의 개발)

  • Lee, Cheol-Eung
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.25 no.2
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    • pp.52-62
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    • 2013
  • A stochastic Markov process (MP) model has been developed for evaluating the probability of failure of the armor unit of rubble-mound breakwaters as a function of time. The mathematical MP model could have been formulated by combining the counting process or renewal process (CP/RP) on the load occurrences with the damage process (DP) on the cumulative damage events, and applied to the armor units of rubble-mound breakwaters. Transition probabilities have been estimated by Monte-Carlo simulation (MCS) technique with the definition of damage level of armor units, and very well satisfies some conditions constrained in the probabilistic and physical views. The probabilities of failure have been also compared and investigated in process of time which have been calculated according to the variations of return period and safety factor being the important variables related to design of armor units of rubble-mound breakwater. In particular, it can be quantitatively found how the prior damage levels can effect on the sequent probabilities of failure. Finally, two types of methodology have been in this study proposed to evaluate straightforwardly the repair times which are indispensable to the maintenance of armor units of rubble-mound breakwaters and shown several simulation results including the cost analyses.

Comparison of Delay Estimates for Signalized Intersection (신호교차로 지체 산정 비교)

  • Jo, Jun-Han;Jo, Yong-Chan;Kim, Seong-Ho
    • Journal of Korean Society of Transportation
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    • v.23 no.1
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    • pp.67-80
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    • 2005
  • In this paper, the primary objective of the research are to review the methods currently avaliable for estimating the delay incurred by vehicles at signalized intersections. The paper compares the delay estimates from a deterministic queueing model, a model based on shock wave theory , the steady-state Webster model, the queue-based models defined in the 1994 and 2001 version of the High way Capacity Manual, in addition to the delays estimated from the TRANSYT-7F macroscopic simulation and NETSIM microscopic simulation. More especially, this paper is to compare the delay estimates obtained using macroscopic and microscopic simulation tools against state-of-the practice analytical models that are derived from deterministic queueing and shock wave analysis theory. The results of the comparisons indicate that all delay models produce relatively similar results for signalized intersections with low traffic demand, but that increasing differences occur as the traffic demand approaches saturation. In particular, when the TRANSYT-7F and NETSIM are compared, it is highly differences as approach for traffic condition to over-saturation. Also, the NETSIM microscopic simulation is the lowest estimates among the various models.

Ruin Probability on Insurance Risk Models (보험위험 확률모형에서의 파산확률)

  • Park, Hyun-Suk;Choi, Jeong-Kyu
    • The Korean Journal of Applied Statistics
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    • v.24 no.4
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    • pp.575-586
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    • 2011
  • In this paper, we study an asymptotic behavior of the finite-time ruin probability of the compound Poisson model in the case that the initial surplus is large. To compare an exact ruin probability with an approximate one, we place the focus on the exact calculation for the ruin probability when the claim size distribution is regularly varying tailed (i.e. exponential claims and inverse Gaussian claims). We estimate an adjustment coefficient in these examples and show the relationship between the adjustment coefficient and the safety premium. The illustration study shows that as the safety premium increases so does the adjustment coefficient. Larger safety premium means lower "long-term risk", which only stands to reason since higher safety premium means a faster rate of safety premium income to offset claims.