• 전기전자학회논문지
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• 제15권1호
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• pp.43-48
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• 2011

본 연구에서는 소프트웨어 제품을 개발하여 테스팅을 거친 후 사용자에게 인도하는 시기를 결정하는 방출문제에 대하여 연구되었다. 무한고장수를 가진 비동질적인 포아송 과정에 기초하고 수명분포는 최소 및 최대값을 적합 시키는데 효율성을 가진 극값 분포를 이용한 최적 방출시기에 관한 문제를 제시하여 소프트웨어 요구 신뢰도를 만족시키고 소프트웨어 개발 및 유지 총비용을 최소화 시키는 최적 소프트웨어 방출 정책에 대하여 논의 되었다. 본 논문의 수치적인 예에서는 고장 간격 시간 자료를 적용하여 기존의 로그 포아송 실행시간 모형과 로그 파우어 모형의 대안으로서 극값 분포모형이 또 하나의 대안이 될 수 있음을 입증하였다.

• Communications for Statistical Applications and Methods
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• 제3권2호
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• pp.249-273
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• 1996

This paper reviews and develops several statistical models for extreme values, based on threshold methodology. Extreme values of a time series are modeled in terms of tails which are defined as truncated forms of original variables, and Markov property is imposed on the tails. Tails of the generalized extreme value distribution and a multivariate extreme value distributively, of the tails of the series. These models are then applied to real ozone data series collected in the Chicago area. A major concern is given to detecting any possible trend in the extreme values.

• Wind and Structures
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• 제26권3호
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

• 한국농공학회논문집
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• 제54권6호
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• pp.45-52
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• 2012

Along with global warming, ever intensifying weather events have increased damages to agricultural farms and facilities. The objective of this study was to investigate the spatial distribution and regional characteristics of agricultural damages by extreme weather events. Agricultural disaster statistics provided by the National Emergency Management Agency were summed over for a 13-year period from 1998 to 2010 and used for the spatial analysis. Two indices of damage area ration and property damage per unit area were introduced to quantify regional agricultural damages. As the results, farm inundation accounted for the largest area primarily damaged by typhoons with heavy rainfalls. Most property damages to farm lands originated from farm erosion in the alpine regions by localized guerrilla rains. The two major causes of damages to greenhouse and livestock facilities were typhoon with strong wind and winter blizzards. Gangwon was the province of the largest property loss mostly from farm land erosion losses, followed by Gyeongnam, Jeonnam, and Chungnam where losses to greenhouse and livestock facilities were relatively greater. Property loss per unit area was also the greatest for the Gangwon province (4.91 M\/ha), followed by Gyongnam and Chungnam of 2.20 and 1.50 M\/ha, respectively. Unit loss for greenhouse and livestock facilities was 13.3 M\/ha, approximately 13 times greater than that for farm land (1.06 M\/ha). The study findings indicated the importance of reducing highland farm erosion and reinforcing farming facilities structures for agricultural disaster management.

• Communications for Statistical Applications and Methods
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• 제31권4호
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• pp.459-466
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• 2024

Multivariate regular variation is a popular framework of multivariate extreme value analysis. However, a suitable parametric model needs to be introduced for efficient estimation of its spectral measure. In such a view, elliptical distributions have been employed for deriving such models. On the other hand, the second order behavior of multivariate regular variation has to be specified for investigating the property of the estimator. This paper derives such a behavior by imposing a widely adopted second order regular variation condition on the representation of elliptical distributions. As result, the second order variation for the convergence to spectral measure is characterized by a signed measure with a regular varying index. Moreover, it leads to the asymptotic bias of the estimator. For demonstration, multivariate t-distribution is considered.

• 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.

• Journal of the Korean Data and Information Science Society
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• 제28권6호
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• pp.1415-1425
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• 2017

태풍은 강한 바람과 폭우를 동반하며 매년 한반도에 인명과 재산피해의 원인이 된다. 국내에서 발생한 자연재해 피해에서 태풍이 차지하는 비중이 높다. 태풍의 많은 피해는 폭우에 의해 발생하므로 태풍이 일 최대강수량에 미치는 영향을 정량적으로 살펴볼 필요가 있다. 일 최대강수량은 극치자료로 일반적으로 일반화극단치분포를 따른다. 연구자료로 1976년부터 2016년까지 한반도에 설치된 60개 종관기상관측장비에서 수집된 일강수량, 최대풍속, 평균풍속 자료가 사용되었다. 태풍이 온 기간을 제외한 일강우량 자료와 태풍이 온 기간을 포함한 일강우량 자료로 구분하여 일반화극단치모형에 적합시켰다. 모수추정방법으로 최우추정법과 L-적률추정법이 이용되었다. K-S검정과 $Cram{\acute{e}}r$ von Mises검정을 통해 모형의 적합도를 검정하였다. 추정된 모수를 기반으로 25년, 50년, 100년, 200년 재현수준을 계산하였다. 태풍기간 포함유무에 따른 재현수준을 비교한 결과 태풍은 강릉 인근의 동해안과 울산과 완도 인근의 남해안의 일 최대강수량에 영향을 미친다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2015년도 춘계 학술논문 발표대회
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• pp.257-258
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• 2015

The amount of damages caused by natural hazards is consistently growing due to the unusual weather and extreme events. At the same time, property damage by natural hazards is rapidly increasing as well. Hence, we need systematic anti-disaster activities and consulting that can react to such a situation. To address these needs, we investigated and analyzed insured claim payouts from natural hazards by administrative area, and calculate the risk index utilizing GIS. According to the index, this map is identifying the areas of greatest natural hazard risk. The ranking of natural disaster vulnerability based on the risk index, and risk grades were divided into five based on the ranking. This map integrates the natural hazard losses to assist in comprehensive and effective loss prevention activities using analysis of regional loss claims from natural hazards. Moreover, this map can be as utilized as loss mitigation and prevention activities to verify the distribution of exposure and hazards.

• Wind and Structures
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• 제38권3호
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• pp.215-229
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• 2024

Guyed mast structures exhibit characteristics such as high flexibility, low mass, small damping ratio, and large aspect ratio, leading to a complex wind-induced vibration response mechanism. This study analyzed the time- and frequency-domain characteristics of the wind-induced response of a guyed mast structure using measured acceleration response data obtained from the Shenzhen Meteorological Gradient Tower (SZMGT). Firstly, 734 sets of 1-hour acceleration samples measured from 0:00 October 1, 2021, to 0:00 November 1, 2021, were selected to study the vibration shapes of the mast and the characteristics of the generalized extreme value (GEV) distribution. Secondly, six sets of typical samples with different vibration intensities were further selected to explore the Gaussian property and modal parameter characteristics of the mast. Finally, the modal parameters of the SZMGT are identified and the identification results are verified by finite element analysis. The findings revealed that the guyed mast vibration shape exhibits remarkable diversity, which increases nonlinearly along the height in most cases and reaches a maximum at the top of the tower. Moreover, the GEV distribution characteristics of the 734 sets of samples are closer to the Weibull distribution. The probability distribution of the structural wind vibration response under strong wind is in good agreement with the Gaussian distribution. The structural response of the mast under wind loading exhibits multiple modes. As the structural response escalates, the first three orders of modal energy in the tower display a gradual increase in proportion.

• 응용통계연구
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• 제24권5호
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• pp.931-939
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• 2011

일반적으로 일반화 파레토 분포(Generalized Pareto Distribution; GPD)에서 임계치를 결정하는 방법으로는 MEF-그래프나 Hill-그래프를 통한 주관적인 판단을 이용한다는 약점이 존재한다. 본 연구에서는 이와 같은 기존 방법의 약점을 해결하기 위하여 GPD에서 임계치를 결정하는 방법으로 로버스트 추정량을 이용하는 새로운 접근 방법을 제안하였다. 더불어 1987년 1월 5일부터 2009년 8월 3일까지 공시된 KOSPI지수의 일별수익률의 손실부분에 해당하는 왼쪽꼬리부분을 이용하여 실증분석을 실시하였다. 실증분석은 기존의 그래프를 이용한 임계치 결정방법과 본 연구에서 제안한 방법에서 계산된 VaR이 어떤 차이가 존재하는가를 알아보는 방법으로 실시되었다. 분석결과 본 논문에서 제안한 임계치 결정방법에 의하여 계산된 VaR값들은 기존 방법의 VaR과 큰 차이를 보이지 않았다. 아울러 본 연구에서 제안한 임계치 결정방법의 안정성을 파악한 결과 기존 방법과 큰 차이를 보이지 않았다. 이와 같은 결과들을 토대로 본 연구에서 제안한 로버스트 추정량을 이용한 임계치 결정방법은 기존의 그래프를 이용한 주관적인 임계치 결정방법에 대한 대안적인 방법으로 충분히 고려될 수 있을 것으로 생각된다.