• Wind and Structures
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• v.19 no.2
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• pp.169-184
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• 2014

This paper presents a method of estimation of extreme wind. Assuming the extreme wind follows the Gumbel distribution, it is modeled through fitting an exponential function to the numbers of storms over different thresholds. The comparison between the estimated results with the Improved Method of Independent Storms (IMIS) shows that the proposed method gives reliable estimation of extreme wind. The proposed method also shows its advantage on the insensitiveness of estimated results to the precision of the data. The volume of extreme storms used in the estimation leads to more than 5% differences in the estimated wind speed with 50-year return period. The annual rate of independent storms is not a significant factor to the estimation.

• Journal of Construction Engineering and Project Management
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• v.4 no.4
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• pp.33-40
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• 2014

Maximizing the profitability and minimizing the duration of construction projects in extreme weather regions is a challenging objective that is essential for project success. An optimization model is presented herein for the time-profit trade-off analysis of construction projects under extreme weather conditions. The model generates optimal/near optimal schedules that maximize profit and minimize the duration of construction projects in extreme weather regions. The computations in the model are organized into: (1) a scheduling module that develops practical schedules for construction projects, (2) a profit module that computes project costs (direct, indirect, and total) and project profit, and (3) a multi-objective module that determines optimal/near optimal trade-offs between project duration and profit. One example is used to show the impact of extreme weather on construction time and profit. Another example is used to show the model's ability to generate optimal trade-offs between the time and profit of construction projects under extreme weather conditions.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.385-388
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• 2008

Recently, occurrence frequency of natural disaster decrease but scale of damage increase remarkably by the Climate change due to global warming. Especially, extreme heat become more critical wether problem in the Korean Peninsula. But, we don't have exact threshold about extreme heat. Therefore, to assess the influences by the extreme heat on personal injury, we analyzed statistics on the causes of the daily mortality. And we developed a threshold for extreme heat health watch warning system.

• Journal of the Korean Mathematical Society
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• v.60 no.1
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• pp.91-113
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• 2023

The polytope of tristochastic tensors of degree three, the Latin polytope, has two kinds of extreme points. Those that are at a maximum distance from the barycenter of the polytope correspond to Latin squares. The remaining extreme points are said to be short. The aim of the paper is to determine the geometry of these short extreme points, as they relate to the Latin squares. The paper adapts the Latin square notion of an intercalate to yield the new concept of a cross-intercalate between two Latin squares. Cross-intercalates of pairs of orthogonal Latin squares of degree three are used to produce the short extreme points of the degree three Latin polytope. The pairs of orthogonal Latin squares fall into two classes, described as parallel and reversed, each forming an orbit under the isotopy group. In the inverse direction, we show that each short extreme point of the Latin polytope determines four pairs of orthogonal Latin squares, two parallel and two reversed.

• Journal of the Korean Mathematical Society
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• v.36 no.3
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• pp.489-507
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• 1999

We investigate the asymptotic behavior of the extreme zeros of orthogonal polynomials with respect to a positive measure d$\alpha$(x) in terms of the three term recurrence coefficients. We then show that the asymptotic behavior of extreme zeros of orthogonal polynomials with respect to g(x)d$\alpha$(x) is the same as that of extreme zeros of orthogonal polynomials with respect to d$\alpha$(x) when g(x) is a polynomial with all zeros in a certain interval determined by d$\alpha$(x). several illustrating examples are also given.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.535-545
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• 2015

In a various range of applications including hydrology, the type-I extreme value distribution has been extensively used as a probabilistic model for analyzing extreme events. In this paper, we introduce methods for estimating the scale parameter of the type-I extreme value distribution. A simulation study is performed to compare the estimators in terms of mean-squared error and bias, and the obtained results are provided.

• Communications of the Korean Mathematical Society
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• v.8 no.1
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• pp.1-14
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• 1993

• Journal of Industrial Technology
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• v.35
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• pp.95-102
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• 2015

Two extreme wind speed prediction models, the EWM(Extreme wind speed model) in IEC61400-1 and the Gumbel method were compared in this study. The two models were used to predict extreme wind speeds of six different sites in Korea and the results were compared with long term wind data. The NCAR reanalysis data were used for inputs to two models. Various periods of input wind data were tried from 1 year to 50 years and the results were compared with the 50 year maximum wind speed of NCAR wind data. It was found that the EWM model underpredicted the extreme wind speed more than 5 % for two sites. Predictions from Gumbel method overpredicted the extreme wind speed or underpredicted it less than 5 % for all cases when the period of the input data is longer than 10 years. The period of the input wind data less than 3 years resulted in large prediction errors for Gumbel method. Predictions from the EWM model were not, however, much affected by the period of the input wind data.

• Wind and Structures
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• v.25 no.3
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• pp.261-282
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• 2017

The probabilistic information of directional extreme wind speeds is important for precisely estimating the design wind loads on structures. A new joint probability distribution model of directional extreme wind speeds is established based on observed wind-speed data using multivariate extreme value theory with the t-Copula function in the present study. At first, the theoretical deficiencies of the Gaussian-Copula and Gumbel-Copula models proposed by previous researchers for the joint probability distribution of directional extreme wind speeds are analysed. Then, the t-Copula model is adopted to solve this deficiency. Next, these three types of Copula models are discussed and evaluated with Spearman's rho, the parametric bootstrap test and the selection criteria based on the empirical Copula. Finally, the extreme wind speeds for a given return period are predicted by the t-Copula model with observed wind-speed records from several areas and the influence of dependence among directional extreme wind speeds on the predicted results is discussed.

• Ocean and Polar Research
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• v.43 no.1
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• pp.1-14
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• 2021

In this study, extreme wind speeds in the Western North Pacific (WNP) were estimated using reanalysis wind fields synthesized with an empirical typhoon vortex model. Reanalysis wind data used is the Fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) data, which was deemed to be the most suitable for extreme value analysis in this study. The empirical typhoon vortex model used has the advantage of being able to realistically reproduce the asymmetric winds of a typhoon by using the gale/storm-forced wind radii information in the 4 quadrants of a typhoon. Using a total of 39 years of the synthesized reanalysis wind fields in the WNP, extreme value analysis is applied to the General Pareto Distribution (GPD) model based on the Peak-Over-Threshold (POT) method, which can be used effectively in case of insufficient data. The results showed that the extreme analysis using the synthesized wind data significantly improved the tendency to underestimate the extreme wind speeds compared to using only reanalysis wind data. Considering the difficulty of obtaining long-term observational wind data at sea, the result of the synthesized wind field and extreme value analysis developed in this study can be used as basic data for the design of offshore structures.