• 제목/요약/키워드: probability model

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결손확률모델에 의한 파손확률 해석에 관한 연구 (A study on the analysis of the failure probability based on the concept of loss probability)

  • 신효철
    • 대한기계학회논문집
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    • 제15권6호
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    • pp.2037-2047
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    • 1991
  • 본 연구에서는 재료 결정격자의 기본단위나 결정립의 형상등 가장 기본적인 형태가 6각형이라는 점에 착안하여 취성재료의 파손모델로 부재들의 결손을 이용하는 결손확률모델을 제안하여 부재결손에 따른 각각의 파손 해석모델과 결손확률을 구한다. 그리고 비결손모델에서 구한 기본인장하중을 기초로 하여 해석하고자 하는 하중하에서 각각의 파손해석모델을 모델링하여 유한요소법으로 부재결손에 따른 요소중심에서의 최대주응력을 구하여 이론극한인장강도와의 비와 결손확률로 취성재료의 파손확률을 구한다. 또한 취성정도에 따른 균열길이에 대한 치수 매개변수를 구함으로써 재료강 도 연구에 기초가 되게 한다.

유도무기 살상효과 산정 모델 및 시각 환경의 개발 ((A Study on the Guided Missile Performance Model and the Development of Visual Environments))

  • 황흥석;정덕길
    • 한국국방경영분석학회지
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    • 제23권1호
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    • pp.1-13
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    • 1997
  • This research investigates a kill probability model for the performance evaluation of guided missile system, and also develops the user interface implementation for the output of the model based on the visual object-oriented programming application. This paper describes in detail the methodology for the kill probability attained by a missile warhead detonating near an airborne target. The major simulation events used in this research are missile guidance homing point, burst points, and kill mechanism(direct kill, blast kill and fragment kill). For the user interface, we also design and implement the visualization system that can show the graphic style of the kill probability attained by the model. This research will bridge the gap between the sophisticated kill probability model and users who want to see the results interactively with visualization, which can benefit many of other military systems. Some examples are shown, but these will be improved to be better with visual simulation which can visualize all the simulation process of the model.

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Estimation Using Response Probability Under Callbacks

  • Park, Hyeon-Ah
    • 한국조사연구학회:학술대회논문집
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    • 한국조사연구학회 2007년도 추계학술대회 발표논문집
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    • pp.213-230
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    • 2007
  • Although the response model has been frequently applied to nonresponse weighting adjustment or imputation, the estimation under callbacks has been relatively underdeveloped in the response model. The estimation method using the response probability is developed under callbacks. A replication method for the estimation of the variance of the proposed estimation is also developed. Since the true response probability is usually unknown, we study the estimation of the response probability. Finally, we propose an estimator under callbacks using the ratio imputation as well as the response probability. The simulation study illustrates our techniques.

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비용과 일정의 결합확률 분포를 적용한 위험비용추정에 관한 연구 (A Study on Cost Risk Estimation applying Joint Cost-Schedule Probability Distribution Model)

  • 김동규;강성진;한규식
    • 한국군사과학기술학회지
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    • 제14권5호
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    • pp.850-858
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    • 2011
  • The risk analysis plays an important role in weapon system acquisition project due to uncertainties in the acquisition process. But in domestic, studies on risk analysis are insufficient and risk cost is not included in acquisition budget in policy. Therefore, in this study, we suggest a method that measures risk or success probability of project using the stochastic model. In particular, in order to calculate the success probability, we apply the joint probability distribution model of cost and schedule that are critical factors influencing the project risk. And also we verify the applicability of this model in Korean defence industry environment through case studies.

분할확률 모델을 이용한 한국어 고립단어 인식 (Isolated Word Recognition Using Segment Probability Model)

  • 김진영;성경모
    • 대한전자공학회논문지
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    • 제25권12호
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    • pp.1541-1547
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    • 1988
  • In this paper, a new model for isolated word recognition called segment probability model is proposed. The proposed model is composed of two procedures of segmentation and modelling each segment. Therefore the spoken word is devided into arbitrary segments and observation probability in each segments is obtained using vector quantization. The proposed model is compared with pattern matching method and hidden Markov model by recognition experiment. The experimental results show that the proposed model is better than exsisting methods in terms of recognition rate and caculation amounts.

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광대역 다중경로 실측채널에서 W-CDMA 수신 신호의 화률 모델 (Probability Models of W-CDMA Signals in Realistic Wideband Multipath Channels)

  • 오동진;이주석;이귀상;김철성
    • 한국통신학회논문지
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    • 제27권4B호
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    • pp.308-315
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    • 2002
  • This paper proposes new probability models for wideband code division multiple access (W-CDMA) signals. The performance of a W-CDMA system is evaluated by calculating the average bit error rate(BER) which is derived from the probability distribution of the W-CDMA receiver output. If a probability model of the receiver output is available, the performance evaluation becomes much simpler and it enables diverse analyses of the system for channel coding and other purposes. In this paper, probability distributions of W-CDMA signals, more specifically those of the receiver output, are represented as Rayleigh and noncentral chi distribution, considering various bandwidths and channel environments. The adequacy of a probability model is verified by chi-square test of 1% significance level. The BER of the system obtained from the simulation results is compared to that obtained from the probability model to demonstrate the usefulness of the proposed models.

이단계 보험요율의 복합 포아송 위험 모형의 파산 확률 (Ruin Probability in a Compound Poisson Risk Model with a Two-Step Premium Rule)

  • 송미정;이지연
    • Communications for Statistical Applications and Methods
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    • 제18권4호
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    • pp.433-443
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    • 2011
  • 잉여금의 수준에 따라 이단계의 보험요율이 적용되는 복합 포아송 위험 모형을 고려한다. 먼저 이 위험 모형에 대응되는 이단계 서비스율의 M/G/1 대기행렬 모형을 설정하고, M/G/1 대기행렬 모형에서 작업량이 0에 도달하기 전에 과부하가 발생하는 확률을 유도한다. 이과부하 확률을 이용하여 위험모형에서 잉여금이 목표값에 도달하기 전에 파산하는 확률을 구하고, 보험 청구액이 지수분포를 따르는 경우의 파산 확률을 계산한다.

은닉마르코브 모델의 부합확률연산의 정수화 알고리즘 개발 (I) (Development of an Integer Algorithm for Computation of the Matching Probability in the Hidden Markov Model (I))

  • 김진헌;김민기;박귀태
    • 전자공학회논문지B
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    • 제31B권8호
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    • pp.11-19
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    • 1994
  • The matching probability P(ο/$\lambda$), of the signal sequence(ο) observed for a finite time interval with a HMM (Hidden Markov Model $\lambda$) indicates the probability that signal comes from the given model. By utilizing the fact that the probability represents matching score of the observed signal with the model we can recognize an unknown signal pattern by comparing the magnitudes of the matching probabilities with respect to the known models. Because the algorithm however uses floating point variables during the computing process hardware implementation of the algorithm requires floating point units. This paper proposes an integer algorithm which uses positive integer numbers rather than float point ones to compute the matching probability so that we can economically realize the algorithm into hardware. The algorithm makes the model parameters integer numbers by multiplying positive constants and prevents from divergence of data through the normalization of variables at each step. The final equation of matching probability is composed of constant terms and a variable term which contains logarithm operations. A scheme to make the log conversion table smaller is also presented. To analyze the qualitive characteristics of the proposed algorithm we attatch simulation result performed on two groups of 10 hypothetic models respectively and inspect the statistical properties with repect to the model order the magnitude of scaling constants and the effect of the observation length.

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Development and Comparison of Data Mining-based Prediction Models of Building Fire Probability

  • 홍성관;정승렬
    • 인터넷정보학회논문지
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    • 제19권6호
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    • pp.101-112
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    • 2018
  • A lot of manpower and budgets are being used to prevent fires, and only a small portion of the data generated during this process is used for disaster prevention activities. This study develops a prediction model of fire occurrence probability based on data mining in order to more actively use these data for disaster prevention activities. For this purpose, variables for predicting fire occurrence probability of various buildings were selected and data of construction administrative system, national fire information system, and Korea Fire Insurance Association were collected and integrated data set was constructed. After appropriate data cleansing and preprocessing, various data mining methodologies such as artificial neural network, decision trees, SVM, and Naive Bayesian were used to develop a prediction model of the fire occurrence probability of buildings. The most accurate model among the derived models is Linear SVM model which shows 68.42% as experimental data and 63.54% as verification data and it is the best model to predict fire occurrence probability of buildings. As this study develops the prediction model which uses only the set values of the specific ranges, future studies may explore more opportunites to use various setting values not shown in this study.

Reference Priors in a Two-Way Mixed-Effects Analysis of Variance Model

  • 장인홍;김병휘
    • Journal of the Korean Data and Information Science Society
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    • 제13권2호
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    • pp.317-328
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    • 2002
  • We first derive group ordering reference priors in a two-way mixed-effects analysis of variance (ANOVA) model. We show that posterior distributions are proper and provide marginal posterior distributions under reference priors. We also examine whether the reference priors satisfy the probability matching criterion. Finally, the reference prior satisfying the probability matching criterion is shown to be good in the sense of frequentist coverage probability of the posterior quantile.

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