• 제목/요약/키워드: time distribution model

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지방부 2차로도로의 차두시간 분포 모델에 관한 연구 (A Study on Headway Distribution Models of Rural Two Lane Roads)

  • 문재필;김동녕
    • 한국도로학회논문집
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    • 제16권1호
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    • pp.49-56
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    • 2014
  • PURPOSES : This study was done to model the headway distribution of rural two lane roads. METHODS : Time headway data for the various level of traffic volumes was measured in twelve sites. Based on the time headway data, existing seven mathematical models were evaluated and selected by comparing graphically the measured and theoretical distributions and conducting the Chi-square test. RESULTS : The results show that both the Schul model and Composite Model were the most appropriate models of the models. Based on the measured time-headway distributions, this study proposed a new headway distribution model by the shift of the Schul model. CONCLUSIONS : The shifted Schul model has the ability to describe time headway distirbutons for random, intermediate, and constant-headway states.

A Bayesian Approach for Accelerated Failure Time Model with Skewed Normal Error

  • Kim, Chansoo
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.268-275
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    • 2003
  • We consider the Bayesian accelerated failure time model. The error distribution is assigned a skewed normal distribution which is including normal distribution. For noninformative priors of regression coefficients, we show the propriety of posterior distribution. A Markov Chain Monte Carlo algorithm(i.e., Gibbs Sampler) is used to obtain a predictive distribution for a future observation and Bayes estimates of regression coefficients.

ASYMPTOTIC DISTRIBUTION OF THE DISCOUNTED PROPER DEFICIT IN THE DISCRETE TIME DELAYED RENEWAL MODEL

  • Bao, Zhen-Hua;Wang, Jing
    • 대한수학회보
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    • 제48권2호
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    • pp.325-334
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    • 2011
  • In this paper we consider the discrete time delayed renewal risk model. We investigate what will happen when the distribution function of the discounted proper deficit is asymptotic in the initial surplus. In doing this we establish several lemmas regarding some related ruin quantities in the discrete time delayed renewal risk model, which are of significance on their own right.

Applying Conventional and Saturated Generalized Gamma Distributions in Parametric Survival Analysis of Breast Cancer

  • Yavari, Parvin;Abadi, Alireza;Amanpour, Farzaneh;Bajdik, Chris
    • Asian Pacific Journal of Cancer Prevention
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    • 제13권5호
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    • pp.1829-1831
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    • 2012
  • Background: The generalized gamma distribution statistics constitute an extensive family that contains nearly all of the most commonly used distributions including the exponential, Weibull and log normal. A saturated version of the model allows covariates having effects through all the parameters of survival time distribution. Accelerated failure-time models assume that only one parameter of the distribution depends on the covariates. Methods: We fitted both the conventional GG model and the saturated form for each of its members including the Weibull and lognormal distribution; and compared them using likelihood ratios. To compare the selected parameter distribution with log logistic distribution which is a famous distribution in survival analysis that is not included in generalized gamma family, we used the Akaike information criterion (AIC; r=l(b)-2p). All models were fitted using data for 369 women age 50 years or more, diagnosed with stage IV breast cancer in BC during 1990-1999 and followed to 2010. Results: In both conventional and saturated parametric models, the lognormal was the best candidate among the GG family members; also, the lognormal fitted better than log-logistic distribution. By the conventional GG model, the variables "surgery", "radiotherapy", "hormone therapy", "erposneg" and interaction between "hormone therapy" and "erposneg" are significant. In the AFT model, we estimated the relative time for these variables. By the saturated GG model, similar significant variables are selected. Estimating the relative times in different percentiles of extended model illustrate the pattern in which the relative survival time change during the time. Conclusions: The advantage of using the generalized gamma distribution is that it facilitates estimating a model with improved fit over the standard Weibull or lognormal distributions. Alternatively, the generalized F family of distributions might be considered, of which the generalized gamma distribution is a member and also includes the commonly used log-logistic distribution.

실무적 적용 관점에서 신뢰성 분포의 유형화 모형의 고찰 (Review of Classification Models for Reliability Distributions from the Perspective of Practical Implementation)

  • 최성운
    • 대한안전경영과학회지
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    • 제13권1호
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    • pp.195-202
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    • 2011
  • The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

물류센터-N 지점 재고시스템의 최적 계획 서비스수준 결정 방법 (A method to determine optimal input service level in a distribution center-N branches inventory distribution system)

  • 윤승철
    • 산업경영시스템학회지
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    • 제20권42호
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    • pp.31-38
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    • 1997
  • The main objective of this research is to develop a model to select the optimal input service level for a distribution center - multi branch inventory distribution system. With the continuous review policy, the distribution center places an order for specific order quantity to an outside supplier, and the order quantity is replenished after a certain lead time. Also, each branch places an order for particular order quantity to the distribution center to satisfy the customer demands, and receives the replenishment after a lead time. When an out of stock condition occurs during an order cycle, a backorder is placed to the upper level to fill the unfilled demands. With these situation, variable demand and variable lead time are used for better industrial practice. Further, actual lead times with a generic lead time distribution are used in developing the control model. Under the actual lead time model, the customer service measures actually attained for the distribution center and each branch are explained as the effective customer service measures. Thus, throughout the optimal control (using computer search procedures), we can select the optimal input service levels for the distribution center and each branch to attain the effective service level for each branch which is consistent with the goal level of service for each branch. At the same time, the entire distribution system keeps minimum inventories.

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유전 알고리듬을 이용한 물류시스템의 동적 수송계획 모형 (A Model of Dynamic Transportation Planning of the Distribution System Using Genetic Algorithm)

  • 장석화
    • 산업경영시스템학회지
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    • 제27권2호
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    • pp.102-113
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    • 2004
  • This paper addresses the transportation planning that is based on genetic algorithm for determining transportation time and transportation amount of minimizing cost of distribution system. The vehicle routing of minimizing the transportation distance of vehicle is determined. A distribution system is consisted of a distribution center and many retailers. The model is assumed that the time horizon is discrete and finite, and the demand of retailers is dynamic and deterministic. Products are transported from distribution center to retailers according to transportation planning. Cost factors are the transportation cost and the inventory cost, which transportation cost is proportional to transportation distance of vehicle when products are transported from distribution center to retailers, and inventory cost is proportional to inventory amounts of retailers. Transportation time to retailers is represented as a genetic string. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. A mathematical model is developed. Genetic algorithm procedure is suggested, and a illustrative example is shown to explain the procedure.

SCM환경에서의 물류센터의 최적 서비스 수준 결정 방법 (A study on the Method to Determine Optimal Service Level of a Distribution Center in Supply Chain Management Environment)

  • 조용욱;박명규
    • 대한안전경영과학회지
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    • 제3권3호
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    • pp.55-64
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    • 2001
  • The main objective of this research is to develop a model to select the optimal input service level for a distribution center-multi branch inventory distribution system. With the continuous review policy, the distribution center places an order for specific order quantity to an outside supplier, and the order quantity is replenished after a certain lead time Also, each branch places an order for particular order quantity to the distribution center to satisfy the customer demands, and receives the replenishment after a lead time. When an out of stock condition occurs during an order cycle, a backorder is placed to the upper level to fill the unfilled demands. With these situation, variable demand and variable lead time are used for better industrial practice. Further, actual lead times with a generic lead time distribution are used in developing the control model. Under the actual lead time model, the customer service measures actually attained for the distribution center and each branch are explained as the effective customer service measures. Thus, throughout the optimal control (using computer search procedures), we can select the optimal input service levels for the distribution center and each branch to attain the effective service levels for each branch which is consistent with the goal level of service for each branch. At the same time, the entire distribution system keeps minimum inventories.

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시간과 능력을 고려한 공급사슬 경영에서의 생산-분배 계획을 위한 시뮬레이션과 최적화모델의 적용 (Production-distribution Planning in Supply Chain Management Considering Processing Times and Capacity Using Simulation and Optimization Model)

  • Sook Han Kim;Young Hae Lee
    • 한국시뮬레이션학회:학술대회논문집
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    • 한국시뮬레이션학회 2000년도 추계학술대회 논문집
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    • pp.165-173
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    • 2000
  • Analytic models have been developed to solve integrated production-distribution problems in supply chain management (SCM). As one of major constraints in analytic models, capacity, which is the total operation time in this paper has mostly been known or disregarded assuming infinite capacity. Also, as major factors, machine processing time to fabricate or assemble a part or product at a certain machine center in production system and vehicle processing time to deliver a product to a customer by a certain vehicle in distribution system have been fixed and regarded as a static factor, But in the real systems significant differences exit between capacity and the required time to achieve the production-distribution plan and between processing time and consumed time to process a part or product. In this paper, capacity and processing times in the analytic model are considered as dynamic factors and adjusted by the results from independently developed simulation model, which includes general production-distribution characteristics. Through experiments, we obtain the more realistic solutions reflecting stochastic natures by performing the iterative analytic-simulation procedure.

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수명분포가 와이블 분포의 형상모수를 고려한 소프트웨어 개발 비용모형에 관한 속성분석 연구 (A Study on Attribute Analysis of Software Development Cost Model about Life Distribution Considering Shape Parameter of Weibull Distribution)

  • 김희철
    • 한국정보전자통신기술학회논문지
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    • 제11권6호
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    • pp.645-650
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    • 2018
  • 소프트웨어 안정성은 운영 환경에서 시간의 흐름에 따른 오작동이 없이 운영 될 수있는 가능성이라고 할 수 있다. 소프트웨어의 고장 분석을 위한 유한 고장 NHPP에서, 고장 발생률은 일정하거나 단조롭게 증가하거나 단조 감소하는 추이를 나타낼 수 있다. 본 연구에서는 NHPP 모형에 근거하고 소프트웨어 고장시간 자료를 바탕으로 와이블 분포의 형상모수를 고려한 지수분포 Rayleigh 분포, 역-지수 분포를 수명분포로 하여 소프트웨어 개발 비용모형에 관한 속성을 비교 평가분석을 하였다. 또한 모수 추정은 최우 추정방법을 적용하고 데이터 추세검정은 박스-플롯방법을 이용하였다. 본 연구의 결과는 Rayleigh 모형이 역-지수 모형이나 Goel-Okumoto 모형에 비교해서 방출 시기는 Rayleigh 모형이 가장 빠르고 방출시점의 비용도 가장 경제적임을 알 수 있다. 이 연구의 결과를 이용하면 소프트웨어 개발자 및 운용자들은 최적방출시간과 경제적인 개발비용을 예측 하는데 활용 할 수 있으리라 판단된다.