• Industrial Engineering and Management Systems
• /
• v.12 no.1
• /
• pp.46-50
• /
• 2013

In insurance statistics, the sum of homogeneous insurance is often needed. The sum is called individual risk model which is a fundamental model in risk analysis for insurance. This paper first presents an individual risk model based on the uncertainty theory. Then its uncertainty distribution is provided. Finally, its arithmetic is shown by a numerical example.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.2
• /
• pp.1-12
• /
• 2009

Distribution centers in a distribution system that consists of the distribution centers and retailers supplies products to retailers. At the present, although total capacity of the distribution centers are enough to supply total demand of retailers, capacity of the distribution centers need to be expanded to satisfy the demand of retailers in case that future demand of the retailers will be increased. Capacity expansion model in a distribution system is to determine the location and size of expansion distribution centers that minimize costs among given distribution centers. Transportation amount from distribution center to retailers also is determined. The costs factors are the capacity expansion costs of the distribution centers and the transportation costs from the distribution centers to the retailers. A model is formulated, and a genetic algorithm based solution procedure is developed. A numerical example is shown and the algorithm is analyzed through examples.

• Journal of Korean Society for Geospatial Information Science
• /
• v.12 no.3 s.30
• /
• pp.43-50
• /
• 2004

This study has an object of searching for appropriateness in applying the trip distribution model by studying the changes of the character of parameter which the model contains and by analyzing and evaluating trip distribution technique out of few steps of pre-estimate technique for the traffic demand through computer simulation centering around Kwangju. Method of this study is investigating the basic theory for trip distribution model and with this grounding, I rearranged it as research data for trip distribution model compatible for Kwangju, using data such as research data on actual state, the statistics annual report and basic plan for traffic full equipment of Kwangju. So, The most stable measure of the type of trip distribution of Kwangju city was produced in Fratar and Detroit model, however, gravity model has a little bit low reliance in sharing of estimation and actual survey although it is astringent in short period.

• Journal of Korean Society of Transportation
• /
• v.4 no.2
• /
• pp.3-14
• /
• 1986

This study was undertaken to develop the gap acceptance model of left-turn drivers on the major road at intersections. Typical unsignalized intersections on the two-lane and four-lane streets in Masan City were selected for the study intersection. For the gap distribution model, the lognormal, negative exponential, shifted negative exponential, and Gamma distributions were tested using the x2 and K-S tests. Based on the results for both streets, it was concluded that among the distributions tested the lognormal distribution represented the gap distribution best, followed by the shifted negative exponential distribution. Stochastic models of the gap-acceptance behavior of left-turn drivers on the major road at unsignalized intersections were programmed using SLAM Ⅱ, a simulation computer language. A stochastic model was selected for the gap-acceptance behavior to compare the results of the simulation with the observed data. The model assumes that a fixed critical acceptance gap is assigned to each left-turn driver based on a normal distribution and the gap distribution of the opposing traffic stream follows the shifted negative exponential distribution.

• Journal of Korean Institute of Industrial Engineers
• /
• v.39 no.2
• /
• pp.109-118
• /
• 2013

We propose a method for estimating coefficients of AR (autoregressive) model which named MLPAR (Maximum Likelihood of Pearson system for Auto-Regressive model). In the present method for estimating coefficients of AR model, there is an assumption that residual or error term of the model follows the normal distribution. In common cases, we can observe that the error of AR model does not follow the normal distribution. So the normal assumption will cause decreasing prediction accuracy of AR model. In the paper, we propose the MLPAR which does not assume the normal distribution of error term. The MLPAR estimates coefficients of auto-regressive model and distribution moments of residual by using pearson distribution system and maximum likelihood estimation. Comparing proposed method to auto-regressive model, results are shown to verify improved performance of the MLPAR in terms of prediction accuracy.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.3
• /
• pp.1-9
• /
• 2014

The inverse Rayleigh model distribution and Rayleigh distribution model were widely used in the field of reliability station. In this paper applied using the finite failure NHPP models in order to growth model. In other words, a large change in the course of the software is modified, and the occurrence of defects is almost inevitable reality. Finite failure NHPP software reliability models can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the inverse Rayleigh and Rayleigh software reliability growth model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, were employed. In order to insurance for the reliability of data, Laplace trend test was employed. In many aspects, Rayleigh distribution model is more efficient than the reverse-Rayleigh distribution model was proved. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can helped.

• Asian Pacific Journal of Cancer Prevention
• /
• v.13 no.5
• /
• pp.1829-1831
• /
• 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.

• Journal of the Korean Statistical Society
• /
• v.26 no.4
• /
• pp.521-530
• /
• 1997

The new Laplace autoregressive model of order 2-NLAR92) studied by Dewald and Lewis (1985) is extended to the p-th order model-NLAR(p). A necessary and sufficient condition for the existence of an innovation sequence and a stationary ergodic NLAR(p) model is obtained. It is shown that the distribution of the innovation sequence is given by the probabilistic mixture of independent Laplace distributions and a degenrate distribution.

• Structural Engineering and Mechanics
• /
• v.80 no.5
• /
• pp.523-538
• /
• 2021

The mechanical behaviour and stability of coal mining engineering underground is significantly affected by ground water. In this study, nuclear magnetic resonance imaging (NMRI) technique was employed to determine the water distribution characteristics in coal specimens during saturation process, based on which the functional rule for water distribution was proposed. Then, using discrete element method (DEM), an innovative numerical modelling method was developed to simulate water-weakening effect on coal behaviour considering moisture content and water distribution. Three water distribution numerical models, namely surface-wetting model, core-wetting model and uniform-wetting model, were established to explore the water distribution influences. The feasibility and validity of the surface-wetting model were further demonstrated by comparing the simulation results with laboratory results. The investigation reveals that coal mechanical properties are affected by both water saturation coefficient and water distribution condition. For all water distribution models, micro-cracks always initiate and nucleate in the water-rich area and thus lead to distinct macro fracture characteristics. With the increase of water saturation coefficient, the failure of coal tends to be less violent with less cracks and ejected fragments. In addition, the core-wetting specimen is more sensitive to water than specimens with other water distribution models.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.33 no.1
• /
• pp.71-79
• /
• 2010

This paper addresses capacity expansion planning model of distribution center under usability of public distribution center. For discrete and finite time periods, demands for distribution center increase dynamically. The capacity expansion planning is to determine the capacity expansion size of private distribution center and usage size of public distribution center for each period through the time periods. The capacity expansion of private distribution center or lease usage of public distribution center must be done to satisfy demand increase for distribution center. The costs are capacity expansion cost and excess capacity holding cost of private distribution center, lease usage cost of public distribution center. Capacity expansion planning of minimizing the total costs is mathematically modelled. The properties of optimal solution are characterized and a dynamic programming algorithm is developed. A numerical example is shown to explain the problem.