• 제목/요약/키워드: Probability Model

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Forecasting Probability of Precipitation Using Morkov Logistic Regression Model

  • Park, Jeong-Soo;Kim, Yun-Seon
    • Communications for Statistical Applications and Methods
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    • 제14권1호
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    • pp.1-9
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    • 2007
  • A three-state Markov logistic regression model is suggested to forecast the probability of tomorrow's precipitation based on the current meteorological situation. The suggested model turns out to be better than Markov regression model in the sense of the mean squared error of forecasting for the rainfall data of Seoul area.

A Study on the Determinants of Free Trade Agreement in South Korea: Evidence from Asian Countries

  • He, Yugang
    • 유통과학연구
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    • 제16권11호
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    • pp.37-45
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    • 2018
  • Purpose - Recently, large quantities of factors have affected the signing of the Free Trade Agreement between two countries. Due to this background, this paper selects South Korea as an example to explore the determinants of Free Trade Agreement from Asian countries. Research design, data, and methodology - A cross sectional data of 2016 will be employed and some variables such as real income and GDP will be used to run an empirical analysis under the linear probability model, probit model and logit model. Results - The findings show that the Asian countries' exchange rate regime, real income, GDP and so forth can increase the probability of signing the Free Trade Agreement with Asian countries. Conversely, the distance can lower the probability of signing the Free Trade Agreement with Asian countries. Meanwhile, although the Asian countries' import, consumer price index and population also can affect the probability of signing the Free Trade Agreement with Asian countries, the estimated coefficients are not statistically significant at 5% level. Conclusions - According to the empirical results, this paper provides a new scope for South Korea's government to sign the Free Trade Agreement with other Asian countries.

경사제 피복재의 유지관리를 위한 추계학적 확률모형 (Stochastic Probability Model for Preventive Management of Armor Units of Rubble-Mound Breakwaters)

  • 이철응;김상욱
    • 대한토목학회논문집
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    • 제33권3호
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    • pp.1007-1015
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    • 2013
  • 하중 발생과정에 따른 누적피해의 선형뿐만 아니라 비선형 거동을 해석할 수 있는 추계학적 확률모형이 수립되었다. 여러 종류의 피해강도함수를 도입하여 내용년수의 파괴확률과 비선형 누적피해의 거동이 자세히 해석되었다. 특히 본 연구에서는 저항한계를 임의의 분포함수를 갖는 확률변수로 취급하여 한계상태의 불확실성을 고려하였다. 또한 피복재에 대한 피해수준을 이용하여 처음으로 추계학적 확률모형을 경사제에 적용하였다. 실험 자료와의 비교를 통해 추정된 경사제 피복재에 대해 피해강도함수를 이용하여 내용년수에 따른 파괴확률과 비선형 누적피해의 거동을 해석하였다. 마지막으로 해석 결과를 이용하여 경사제 피복재의 보수 보강 시점과 최소한의 보수 보강규모를 정량적으로 산정할 수 있는 예방적 유지관리 방법을 제시하였다.

Prediction of the Probability of Customer Attrition by Using Cox Regression

  • Kang, Hyuncheol;Han, Sang-Tae
    • Communications for Statistical Applications and Methods
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    • 제11권2호
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    • pp.227-233
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    • 2004
  • This paper presents our work on constructing a model that is intended to predict the probability of attrition at specified points in time among customers of an insurance company. There are some difficulties in building a data-based model because a data set may contain possibly censored observations. In an effort to avoid such kind of problem, we performed logistic regression over specified time intervals while using explanatory variables to construct the proposed model. Then, we developed a Cox-type regression model for estimating the probability of attrition over a specified period of time using time-dependent explanatory variables subject to changes in value over the course of the observations.

한국어 구어 음성 언어 이해 모델에 관한 연구 (A Study on Korean Spoken Language Understanding Model)

  • 노용완;홍광석
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.2435-2438
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    • 2003
  • In this paper, we propose a Korean speech understanding model using dictionary and thesaurus. The proposed model search the dictionary for the same word with in input text. If it is not in the dictionary, the proposed model search the high level words in the high level word dictionary based on the thesaurus. We compare the probability of sentence understanding model with threshold probability, and we'll get the speech understanding rate. We evaluated the performance of the sentence speech understanding system by applying twenty questions game. As the experiment results, we got sentence speech understanding accuracy of 79.8%. In this case probability of high level word is 0.9 and threshold probability is 0.38.

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A Probabilistic Fuzzy Logic Approach to Identify Productivity Factors in Indian Construction Projects

  • Princy, J. Darwin;Shanmugapriya, S.
    • Journal of Construction Engineering and Project Management
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    • 제7권3호
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    • pp.39-55
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    • 2017
  • Preeminent performance of construction industry are unattainable with poor productivity resulting in time and cost over runs. Enhancement in productivity cannot be achieved without identifying and analyzing factors that adversely affect productivity. The objective therefore is to propose a productivity analysis model to quantify the probability of effect of factors influencing productivity by using fuzzy logic incorporated with relative importance index method, for various types of construction projects. To achieve this objective, a questionnaire survey was carried out targeting respondents of Indian construction industry, from four distinct projects, namely, residential, commercial, infrastructure and industrial projects. Based on questionnaire administered, the relative importance and ranks of factors demonstrated using relative importance index method. Probability assessment model to analyze productivity was then developed by using Fuzzy Logic Toolbox of MATLAB. The applicability of the proposed model was tested in seven construction projects and the probability of impact of factors on productivity evaluated. The results of application of model in the construction firms infers that the most contributing factor groups for most of the projects were discerned to be manpower, motivation and time group.

확률함수를 이용한 비균질 Ti-6Al-4V 합금의 변형 및 파손해석 (Deformation and Failure Analysis of Heterogeneous Microstructures of Ti-6Al-4V Alloy using Probability Functions)

  • 김태원;고은영
    • 대한기계학회논문집A
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    • 제28권6호
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    • pp.685-692
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    • 2004
  • A stochastic approach has been presented for superplastic deformation of Ti-6Al-4V alloy, and probability functions are used to model the heterogeneous phase distributions. The experimentally observed spatial correlation functions are developed, and microstructural evolutions together with superplastic deformation behavior have been investigated by means of the two-point and three-point probability functions. The results have shown that the probability varies approximately linearly with separation distance, and deformation enhanced probability changes during the process. The stress-strain behavior with the evolutions of probability function can be correctly predicted by the model. The finite element implementation using Monte Carlo simulation associated with reconstructed microstructures shows that better agreement with experimental data of failure strain on the test specimen.

Empirical seismic fragility rapid prediction probability model of regional group reinforced concrete girder bridges

  • Li, Si-Qi;Chen, Yong-Sheng;Liu, Hong-Bo;Du, Ke
    • Earthquakes and Structures
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    • 제22권6호
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    • pp.609-623
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    • 2022
  • To study the empirical seismic fragility of a reinforced concrete girder bridge, based on the theory of numerical analysis and probability modelling, a regression fragility method of a rapid fragility prediction model (Gaussian first-order regression probability model) considering empirical seismic damage is proposed. A total of 1,069 reinforced concrete girder bridges of 22 highways were used to verify the model, and the vulnerability function, plane, surface and curve model of reinforced concrete girder bridges (simple supported girder bridges and continuous girder bridges) considering the number of samples in multiple intensity regions were established. The new empirical seismic damage probability matrix and curve models of observation frequency and damage exceeding probability are developed in multiple intensity regions. A comparative vulnerability analysis between simple supported girder bridges and continuous girder bridges is provided. Depending on the theory of the regional mean seismic damage index matrix model, the empirical seismic damage prediction probability matrix is embedded in the multidimensional mean seismic damage index matrix model, and the regional rapid prediction matrix and curve of reinforced concrete girder bridges, simple supported girder bridges and continuous girder bridges in multiple intensity regions based on mean seismic damage index parameters are developed. The established multidimensional group bridge vulnerability model can be used to quantify and predict the fragility of bridges in multiple intensity regions and the fragility assessment of regional group reinforced concrete girder bridges in the future.

Deriving Probability Models for Stress Analysis

  • Ahn Suneung
    • 한국산업경영시스템학회:학술대회논문집
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    • 한국산업경영시스템학회 2002년도 춘계학술대회
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    • pp.139-149
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    • 2002
  • This paper presents an approach to derive probability models for use in structural reliability studies. Two main points are made. First, that it is possible to translate engineering and physics knowledge into a requirement on the form of a probability model. And second, that making assumptions about a probability model for structural failure implies either explicit or hidden assumptions about material and structural properties. The work is foundational in nature, but is developed with explicit examples taken from planar and general stress problems, the von Mises failure criterion, and a modified Weibull distribution.

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확률분포추정기법을 이용한 유도전동기의 모델기반 고장진단 알고리즘 개발 (Model based Fault Detection and Diagnosis of Induction Motors using Probability Density Estimation)

  • 김광수;이영진;송헌혜;이권순
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 춘계학술대회 논문집 전기설비전문위원
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    • pp.171-173
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    • 2008
  • This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

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