• 한국해안해양공학회:학술대회논문집
• /
• 한국해안해양공학회 2006년도 추계학술대회 발표논문집 Proceedings of Coastal and Ocean Engineering in Korea
• /
• pp.65-68
• /
• 2006

• Wind and Structures
• /
• 제31권5호
• /
• pp.419-430
• /
• 2020

Weibull distribution is a conspicuous distribution known for its accuracy and its usage for wind energy analysis. The two and three parameter Weibull distributions are adopted in this study to fit wind speed data. The daily mean wind speed data of Ennore, Tamil Nadu, India has been used to validate the procedure. The parameters are estimated using maximum likelihood method, least square method and moment method. Four statistical tests namely Root mean square error, R2 test, Kolmogorov-Smirnov test and Anderson-Darling test are employed to inspect the fitness of Weibull probability density functions. The value of shape factor, scale factor, wind speed and wind power are determined at a height of 100m using extrapolation of numerical equations. Also, the value of capacity factor is calculated mathematically. This study provides a way to evaluate feasible locations for wind energy assessment, which can be used at any windy site throughout the world.

• 충청수학회지
• /
• 제27권2호
• /
• pp.243-247
• /
• 2014

Let {$X_n$, $n{\geq}1$} be a sequence of i.i.d. random variables with absolutely continuous cumulative distribution function(cdf) F(x) and the corresponding probability density function(pdf) f(x). In this paper, we give characterizations of Pareto and Weibull distribution by considering conditional expectations of record values.

• 품질경영학회지
• /
• 제28권3호
• /
• pp.1-10
• /
• 2000

In this paper, we address the Bayesian hypotheses testing for the comparison of Weibull distributions. In Bayesian testing problem, conventional Bayes factors can not typically accommodate the use of noninformative priors which are Improper and are defined only up to arbitrary constants. To overcome such problem, we use the recently proposed hypotheses testing criterion called the intrinsic Bayes factor. We derive the arithmetic and median intrinsic Bayes factors for the comparison of Weibull lifetime model and we use these results to analyze real data sets.

• Journal of the Korean Statistical Society
• /
• 제28권3호
• /
• pp.359-370
• /
• 1999

We considered a change-point hazard rate model generalizing constant hazard rate model. This type of model is very popular in the sense that the Weibull and exponential distributions formulating survival time data are the special cases of it. Maximum likelihood estimation and the asymptotic properties such as the consistency and its limiting distribution of the change-point estimator were discussed. A parametric bootstrap method for finding confidence intervals of the unknown change-point was also suggested and the proposed method is explained through a practical example.

• Journal of the Korean Statistical Society
• /
• 제34권1호
• /
• pp.11-20
• /
• 2005

The distributional properties of R = X/(X + Y) and related estimation procedures are derived when X and Y are independent and identically distributed according to the Weibull or Levy distribution. The work is of interest in biological and physical sciences, econometrics, engineering and ranking and selection.

• The Korean Journal of Ecology
• /
• 제23권6호
• /
• pp.435-438
• /
• 2000

Diameter distributions describe forest stand structure information. Prediction equations for percentiles of diameter distribution and parameter recovery procedures for the Weibull distribution function based on four percentile equations were applied to develop prediction system of even-aged slash pine stand structure development in terms of the number of stems per diameter class changes. Four percentiles of the cumulative diameter distribution were predicted as a function of stand characteristics. The predicted diameter distributions were tested against the observed diameter distributions using the Kolmogorov-Smirnov two sample test at the ${\alpha}$=0.05 level. Statistically, no significant differences were detected based on the data from 236 evaluation data sets. This stand level diameter distribution prediction system will be useful in slash pine stand structure modeling and in updating forest inventories for the long-term forest management planning.

• Journal of the Korean Data and Information Science Society
• /
• 제20권3호
• /
• pp.485-492
• /
• 2009

본 연구에서는 소형 승용차용 브레이크 패드 공정의 공정능력분석과 패드의 마모수명 분포를 실제데이터를 이용하여 추정하였다. 정규분포와 2모수 와이블분포 및 로지스틱분포 모두 마모수명데이터를 적합한다고 분석되었다. 추정된 수명 분포로부터 얻어진 백분위 수명은 브레이크 패드의 설계기준 설정이나 고객의 품질요구수준 평가에 활용될 수 있을 것이다.

• International Journal of Naval Architecture and Ocean Engineering
• /
• 제11권1호
• /
• pp.165-177
• /
• 2019

This paper considers corrosion wastage of two ship hull structure members as a part of investigated fuel oil tanks of 25 aging bulk carriers. Taking into account that many factors which influence corrosion wastage of ship hull structures are of uncertain nature, the related corrosion rate ($c_1$) is considered here as a real-valued continuous distribution, assuming that the corrosion wastage starts after 5, 6 or 7 years. In all considered cases, by using available data and applying three basic statistical tests, it is established that between two-parameter continuous distributions, normal, Weibull and logistic distributions are best fitted distributions for the mentioned corrosion rate ($c_1$). Note that the presented statistical, numerical and graphical results concerning two mentioned ship hull structure members allow to compare and discuss the corresponding probabilistic estimates for the corrosion rate ($c_1$).

• 한국전기전자재료학회논문지
• /
• 제30권9호
• /
• pp.551-557
• /
• 2017

It is extremely important to improve methodologies for the lifetime assessment of porcelain insulators. While there has been a considerable amount of work regarding the phenomena of lifetime distributions, most of the studies assume that aging distributions follow the Weibull distribution. However, the true underlying distribution is unknown, giving rise to unrealistic inferences, such as parameter estimations. In this article, we review several distributions that are commonly used in reliability and survival analysis, such as the exponential, Weibull, log-normal, and gamma distributions. Some properties, including the characteristics of failure rates of these distributions, are presented. We use a Bayesian approach for model selection and parameter estimation procedures. A well-known measure, called the Bayes factor, is used to find the most plausible model among several contending models. The posterior mean can be used as a parameter estimate for unknown parameters, once a model with the highest posterior probability is selected. Extensive simulation studies are performed to demonstrate our methodologies.