• 제목/요약/키워드: Generalized extreme value (GEV) distribution

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비정상성 확률분포 및 재현기간을 고려한 홍수빈도분석 (Flood Frequency Analysis Considering Probability Distribution and Return Period under Non-stationary Condition)

  • 김상욱;이영섭
    • 한국수자원학회논문집
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    • 제48권7호
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    • pp.567-579
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    • 2015
  • 본 연구에서는 모수(parameter)가 시간에 따라 변화하는 비정상성 확률분포를 훙수빈도분석에 적용하였다. 또한, 비정상성을 가정한 재현기간 및 위험도를 추정하였다. GEV (Generalized Extreme Value) 분포를 사용하여 정상성 및 비정상성 모형 4개를 구축하였으며 비정상성 모형은 위치모수(location parameter)만 선형경향성을 가지는 경우, 규모모수(scale parameter)만 선형경향성을 가지는 경우, 위치 및 규모모수가 모두 선형경향성을 가지는 경우의 3가지로 구분되었다. 구축된 4개의 모형 중 적합모형을 선정하기 위해 상대적 우도비 검정과 Akaike 정보기준을 사용하였으며, 우리나라의 8개 다목적댐(충주댐, 소양강댐, 안동댐, 임하댐, 합천댐, 대청댐, 섬진강댐, 주암댐)으로부터 취득된 과거 관측 댐 유입량을 사용하여 제안된 절차를 적용하고 결과를 비교분석하였다. 적합모형 선정 결과 합천댐과 섬진강댐이 비정상성 GEV 모형에 적합한 것으로 분석되었고, 나머지 6개 지점의 다목적댐들은 정상성 모형에 적합한 것으로 분석되었다. 특히 합천댐과 섬진강댐의 경우 비정상성 가정에서 산정된 재현기간이 정상성 가정에서 산정된 재현기간보다 작게 산정되었음을 알 수 있었다.

Probabilistic analysis of gust factors and turbulence intensities of measured tropical cyclones

  • Tianyou Tao;Zao Jin;Hao Wang
    • Wind and Structures
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    • 제38권4호
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    • pp.309-323
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    • 2024
  • The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cable-stayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications.

고차확률가중모멘트법에 의한 지역화빈도분석과 GIS기법에 의한 설계강우량 추정(II) - L-모멘트법을 중심으로 - (Estimation of Design Rainfall by the Regional Frequency Analysis using Higher Probability Weighted Moments and GIS Techniques(l ) - On the method of L-moments-)

  • 이순혁;박종화;류경식
    • 한국농공학회지
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    • 제43권5호
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    • pp.70-82
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    • 2001
  • This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation suggested by the first report of this project. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the Generalized extreme value distribution among applied distributions. Regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error(RRMSE), relative bias(RBIAS) and relative reduction(RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the legions and consecutive durations were derived by the regional frequency analysis.

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A study on the optimal equation of the continuous wave spectrum

  • Cho, Hong-Yeon;Kweon, Hyuck-Min;Jeong, Weon-Mu;Kim, Sang-Ik
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제7권6호
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    • pp.1056-1063
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    • 2015
  • Waves can be expressed in terms of a spectrum; that is, the energy density distribution of a representative wave can be determined using statistical analysis. The JONSWAP, PM and BM spectra have been widely used for the specific target wave data set during storms. In this case, the extracted wave data are usually discontinuous and independent and cover a very short period of the total data-recording period. Previous studies on the continuous wave spectrum have focused on wave deformation in shallow water conditions and cannot be generalized for deep water conditions. In this study, the Generalized Extreme Value (GEV) function is proposed as a more-optimal function for the fitting of the continuous wave spectral shape based on long-term monitored point wave data in deep waters. The GEV function was found to be able to accurately reproduce the wave spectral shape, except for discontinuous waves of greater than 4 m in height.

GEV 분포를 이용한 대구·경북 지역 일산화탄소 농도 추정 (The estimation of CO concentration in Daegu-Gyeongbuk area using GEV distribution)

  • 류수락;엄은진;권태용;윤상후
    • Journal of the Korean Data and Information Science Society
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    • 제27권4호
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    • pp.1001-1012
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    • 2016
  • 대기오염물질이 인간의 건강에 악영향을 미치는 사실은 잘 알려져 있다. 유엔 환경 계획 (united nations environment program; UNEP) 보고서에 따르면, 미세먼지와 일산화탄소 오염물질로 연간 전 세계에서 430만 명이 목숨을 잃었다. 일산화탄소는 탄소와 산소로 구성된 화합물로 가정에서 생성되는 독성 가스 중 가장 위험한 가스이다. 연구를 위하여 2004년부터 2013년까지 10년간 대구 경북 지역의 대기오염관측소에서 관측된 1시간, 6시간, 12시간, 24시간 평균 일산화탄소 농도 자료를 사용하였다. 일반화 극단치 분포의 모수는 최우추정법과 L-적률추정법을 통해 추정하였고 적합도 검정을 수행하였다. 본 연구의 표본 수가 크지 않으므로 L-적률추정법이 최대우도법에 비해 모수추정에 적합하였다. 또한, 5년, 10년, 20년, 40년 재현수준을 추정하여 대구 경북 지역 일산화탄소 위험지역을 살펴보았다.

L 및 LH-모멘트법과 지역빈도분석에 의한 가뭄우량의 추정 (II)- LH-모멘트법을 중심으로 - (Estimation of Drought Rainfall by Regional Frequency Analysis Using L and LH-Moments (II) - On the method of LH-moments -)

  • 이순혁;윤성수;맹승진;류경식;주호길;박진선
    • 한국농공학회논문집
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    • 제46권5호
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    • pp.27-39
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    • 2004
  • In the first part of this study, five homogeneous regions in view of topographical and geographically homogeneous aspects except Jeju and Ulreung islands in Korea were accomplished by K-means clustering method. A total of 57 rain gauges were used for the regional frequency analysis with minimum rainfall series for the consecutive durations. Generalized Extreme Value distribution was confirmed as an optimal one among applied distributions. Drought rainfalls following the return periods were estimated by at-site and regional frequency analysis using L-moments method. It was confirmed that the design drought rainfalls estimated by the regional frequency analysis were shown to be more appropriate than those by the at-site frequency analysis. In the second part of this study, LH-moment ratio diagram and the Kolmogorov-Smirnov test on the Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distributions were accomplished to get optimal probability distribution. Design drought rainfalls were estimated by both at-site and regional frequency analysis using LH-moments and GEV distribution, which was confirmed as an optimal one among applied distributions. Design rainfalls were estimated by at-site and regional frequency analysis using LH-moments, the observed and simulated data resulted from Monte Carlotechniques. Design drought rainfalls derived by regional frequency analysis using L1, L2, L3 and L4-moments (LH-moments) method have shown higher reliability than those of at-site frequency analysis in view of RRMSE (Relative Root-Mean-Square Error), RBIAS (Relative Bias) and RR (Relative Reduction) for the estimated design drought rainfalls. Relative efficiency were calculated for the judgment of relative merits and demerits for the design drought rainfalls derived by regional frequency analysis using L-moments and L1, L2, L3 and L4-moments applied in the first report and second report of this study, respectively. Consequently, design drought rainfalls derived by regional frequency analysis using L-moments were shown as more reliable than those using LH-moments. Finally, design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were derived by regional frequency analysis using L-moments, which was confirmed as a more reliable method through this study. Maps for the design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were accomplished by the method of inverse distance weight and Arc-View, which is one of GIS techniques.

우리나라 연최대강우량의 지형학적 특성 및 이에 근거한 최적확률밀도함수의 산정 (Geographical Impact on the Annual Maximum Rainfall in Korean Peninsula and Determination of the Optimal Probability Density Function)

  • 남윤수;김동균
    • 한국습지학회지
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    • 제17권3호
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    • pp.251-263
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    • 2015
  • 본 연구에서는 L-moment ratio diagram 기법과 지형정보시스템(GIS)을 동시에 활용하여 우리나라의 지속기간별 연 최대강우량의 최적확률밀도함수를 판별하는 새로운 기법을 제안하고, 결과 도출과정에 있어 발견된 연최대강우량의 통계값의 흥미로운 지형학적 특성을 살펴보았다. 이를 위하여 우리나라 기상청에서 운영하는 67개의 강우관측지점에서 관측된 강우자료의 연최대강우량을 1시간, 3시간, 6시간, 12시간, 24시간 누적시간에 대하여 산출하고, L-moment ratio diagram 기법을 활용하여 이들에 대한 최적확률밀도함수를 구한 후, 이를 관측지점에 해당하는 티센 다각형에 다른 색상으로 표현하여 그 공간적 분포를 살펴보았다. 또한, 각 후보 확률밀도함수의 적합도에 대한 지도를 작성하였다. 본 연구의 결과를 요약하면 다음과 같다: (1) 강우의 극한값의 특성을 대표할 수 있는 통계값인 L-skewness와 L-kurtosis는 뚜렷한 공간적 경향을 띠고 있다. 특히 산맥을 포함한 우리나라의 지형적 특성에 큰 영향을 받았다. 이는 발생빈도가 높고 강도가 낮은 평상시의 강우사상뿐 만 아니라, 연최대강우량 또한 지형의 영향을 크게 받는다는 것을 의미한다; (2) 우리나라의 산악지역에서는 연최대강우량의 통계적 특성에 대한 고도의 영향이 비산악지역보다 더 크며, 고도가 높은 지역일수록 발생 빈도가 낮고 강도가 강한 강우사상이 더 자주 발생하며, 강우의 누적기간이 증가할수록 이러한 경향은 작아졌다; (3) 우리나라의 연최대강우량을 가장 잘 대변할 수 있는 확률밀도함수는 Generalized Extreme Value (GEV) 분포와 Generalized Logistic (GLO) 분포이다. 단, 남해안의 중앙지역에 대해서는 Generalized Pareto (GPA) 분포가 가장 적합한 것으로 나타났다.

Non-stationary statistical modeling of extreme wind speed series with exposure correction

  • Huang, Mingfeng;Li, Qiang;Xu, Haiwei;Lou, Wenjuan;Lin, Ning
    • 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.

LH-모멘트의 적정 차수 결정에 의한 설계홍수량 추정(II) (Estimation of Design Flood by the Determination of Best Fitting Order of LH-Moments(II))

  • 맹승진;이순혁
    • 한국농공학회지
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    • 제45권1호
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    • pp.33-44
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    • 2003
  • This study was conducted to estimate the design flood by the determination of best fitting order for LH-moments of the annual maximum series at fifteen watersheds. Using the LH-moment ratios and Kolmogorov-Smirnov test, the optimal regional probability distribution was identified to be the Generalized Extreme Value (GEV) in the first report of this project. Parameters of GEV distribution and flood flows of return period n years were derived by the methods of L, L1, L2, L3 and L4-moments. Frequency analysis of flood flow data generated by Monte Carlo simulation was performed by the methods of L, L1, L2, L3 and L4-moments using GEV distribution. Relative Root Mean Square Error. (RRMSE), Relative Bias (RBIAS) and Relative Efficiency (RE.) using methods of L, Ll , L2, L3 and L4-moments for GEV distribution were computed and compared with those resulting from Monte Carlo simulation. At almost all of the watersheds, the more the order of LH-moments and the return periods increased, the more RE became, while the less RRMSE and RBIAS became. The Absolute Relative Reduction (ARR) for the design flood was computed. The more the order of LH-moments increased, the less ARR of all applied watershed became It was confirmed that confidence efficiency of estimated design flood was increased as the order of LH-moments increased. Consequently, design floods for the appled watersheds were derived by the methods of L3 and L4-moments among LH-moments in view of high confidence efficiency.

L-모멘트법에 의한 강우의 지역빈도분석 (Regional Frequency Analysis for Rainfall using L-Moment)

  • 고덕구;추태호;맹승진;찬다트리베디
    • 한국콘텐츠학회논문지
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    • 제8권3호
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    • pp.252-263
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    • 2008
  • 본 연구에서는 L-모멘트법에 의한 지역화 빈도분석에 따른 설계강우량 추정에 관한 연구를 수행하였다. 제주도와 울릉도의 강우관측소를 제외한 분석에 사용된 65개 강우관측소의 강우자료 수집과 선정된 강우관측지점의 강우자료의 지속시간, 즉 1, 3, 6, 12, 24, 36, 48 및 72시간 지속의 연최대치 계열을 구성하였다. 관측지점을 대상으로 Cluster분석을 실시한 결과 우리나라의 강우관측지점에 대한 합리적인 지역화로 5개의 지역으로 구분되었다. 지역화된 지역에 대한 지속기간별 극치강우자료의 적정분포모형 결정을 위한 6가지 분포모형의 적용하고 적용분포의 L-모멘트비를 산정하여 L-모멘트비도를 도시하고 K-S 검정에 의한 적정분포모형을 선정하였다. 선정된 적정분포는 GEV 분포이며 이 분포에 의해 강우관측치의 점빈도 및 지역빈도분석에 의한 설계강우량을 유도하였다. Monte Carlo 기법에 의해 모의발생된 강우량의 점빈도 및 지역빈도분석에 의한 설계강우량을 유도하였다. 실측치 및 모의발생치의 점빈도 및 지역빈도분석에 의한 설계강우량의 비교분석을 위해 상대제곱근오차와 상대편의오차에 의해 분석한 결과 점빈도 분석에 의한 설계강우량보다 지역빈도분석에 의한 설계강우량의 사용이 적정한 것으로 나타났다.