• Title/Summary/Keyword: general extreme value distribution

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Distribution of the Estimator for Peak of a Regression Function Using the Concomitants of Extreme Oder Statistics

  • Kim, S.H;Kim, T.S.
    • Communications for Statistical Applications and Methods
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    • v.5 no.3
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    • pp.855-868
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    • 1998
  • For a random sample of size n from general linear model, $Y_i= heta(X_i)+varepsilon_i,;let Y_{in}$ denote the ith oder statistics of the Y sample values. The X-value associated with $Y_{in}$ is denoted by $X_{[in]}$ and is called the concomitant of ith order statistics. The estimator of the location of a maximum of a regression function, $ heta$($\chi$), was proposed by (equation omitted) and was found the convergence rate of it under certain weak assumptions on $ heta$. We will discuss the asymptotic distributions of both $ heta(X_{〔n-r+1〕}$) and (equation omitted) when r is fixed as nolongrightarrow$\infty$(i.e. extreme case) on the basis of the theorem of the concomitants of order statistics. And the will investigate the asymptotic behavior of Max{$\theta$( $X_{〔n-r+1:n〕/}$ ), . , $\theta$( $X_{〔n:n〕}$)}as an estimator for the peak of a regression function.

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The Assessment of Future Flood Vulnerability for Seoul Region (서울 지역의 미래 홍수취약도 평가)

  • Sung, Jang Hyun;Baek, Hee-Jeong;Kang, Hyun-Suk;Kim, Young-Oh
    • Journal of Wetlands Research
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    • v.14 no.3
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    • pp.341-352
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    • 2012
  • The purpose of this study is to statistically project future probable rainfall and to quantitatively assess a future flood vulnerability using flood vulnerability model. To project probable rainfall under non-stationarity conditions, the parameters of General Extreme Value (GEV) distribution were estimated using the 1 yr data added to the initial 30 yr base series. We can also fit a linear regression model between time and location parameters after comparing the linear relationships between time and location, scale, and shape parameters, the probable rainfall in 2030 yr was calculated using the location parameters obtained from linear regression equation. The flood vulnerability in 2030 yr was assessed inputted the probable rainfall into flood vulnerability assessment model suggested by Jang and Kim (2009). As the result of analysis, when a 100 yr rainfall frequency occurs in 2030 yr, it was projected that vulnerability will be increased by spatial average 5 % relative to present.

Spatial distribution and uncertainty of daily rainfall for return level using hierarchical Bayesian modeling combined with climate and geographical information (기후정보와 지리정보를 결합한 계층적 베이지안 모델링을 이용한 재현기간별 일 강우량의 공간 분포 및 불확실성)

  • Lee, Jeonghoon;Lee, Okjeong;Seo, Jiyu;Kim, Sangdan
    • Journal of Korea Water Resources Association
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    • v.54 no.10
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    • pp.747-757
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    • 2021
  • Quantification of extreme rainfall is very important in establishing a flood protection plan, and a general measure of extreme rainfall is expressed as an T-year return level. In this study, a method was proposed for quantifying spatial distribution and uncertainty of daily rainfall depths with various return periods using a hierarchical Bayesian model combined with climate and geographical information, and was applied to the Seoul-Incheon-Gyeonggi region. The annual maximum daily rainfall depth of six automated synoptic observing system weather stations of the Korea Meteorological Administration in the study area was fitted to the generalized extreme value distribution. The applicability and reliability of the proposed method were investigated by comparing daily rainfall quantiles for various return levels derived from the at-site frequency analysis and the regional frequency analysis based on the index flood method. The uncertainty of the regional frequency analysis based on the index flood method was found to be the greatest at all stations and all return levels, and it was confirmed that the reliability of the regional frequency analysis based on the hierarchical Bayesian model was the highest. The proposed method can be used to generate the rainfall quantile maps for various return levels in the Seoul-Incheon-Gyeonggi region and other regions with similar spatial sizes.

Determination of Proper Probability Distribution for Groundwater Monitoring Stations in Jeju Island (제주도 지하수위 관측지점별 적정 확률분포형의 결정)

  • Chung, Il-Moon;Nam, Woosung;Kim, Min Gyu;Choi, Gian;Kim, Gee-Pyo;Park, Yun-Seok
    • Journal of Soil and Groundwater Environment
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    • v.23 no.1
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    • pp.41-53
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    • 2018
  • Comprehensive statistical analysis for the 127 groundwater monitoring stations in Jeju Island during 2005~2015 was carried out for the re-establishment of management groundwater level. Three probability distribution functions such as normal distibution, GEV (General Extreme Value) distribution, and Gumbel distribution were applied and the maximum likelihood method was used for parameter estimation of each distribution. AIC (Akaike information criterion) was calculated based on the estimated parameters to determine the proper probability distribution for all 127 stations. The results showed that normal distribution and Gumble distribution were found in 11 stations. Whereas GEV distribution were found in 105 stations, which covered most of groundwater monitoring stations. Therefore, confidence levels should be established in accord with the proper probability distribution when groundwater level management is determined.

A study on the working mechanism of internal pressure of super-large cooling towers based on two-way coupling between wind and rain

  • Ke, Shitang;Yu, Wenlin;Ge, Yaojun
    • Structural Engineering and Mechanics
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    • v.70 no.4
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    • pp.479-497
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    • 2019
  • In the current code design, the use of a uniform internal pressure coefficient of cooling towers as internal suction cannot reflect the 3D characteristics of flow field inside the tower body with different ventilation rate of shutters. Moreover, extreme weather such as heavy rain also has a direct impact on aerodynamic force on the internal surface and changes the turbulence effect of pulsating wind. In this study, the world's tallest cooling tower under construction, which stands 210m, is taken as the research object. The algorithm for two-way coupling between wind and rain is adopted. Simulation of wind field and raindrops is performed iteratively using continuous phase and discrete phase models, respectively, under the general principles of computational fluid dynamics (CFD). Firstly, the rule of influence of 9 combinations of wind speed and rainfall intensity on the volume of wind-driven rain, additional action force of raindrops and equivalent internal pressure coefficient of the tower body is analyzed. The combination of wind velocity and rainfall intensity that is most unfavorable to the cooling tower in terms of distribution of internal pressure coefficient is identified. On this basis, the wind/rain loads, distribution of aerodynamic force and working mechanism of internal pressures of the cooling tower under the most unfavorable working condition are compared between the four ventilation rates of shutters (0%, 15%, 30% and 100%). The results show that the amount of raindrops captured by the internal surface of the tower decreases as the wind velocity increases, and increases along with the rainfall intensity and ventilation rate of the shutters. The maximum value of rain-induced pressure coefficient is 0.013. The research findings lay the basis for determining the precise values of internal surface loads of cooling tower under extreme weather conditions.

Observational study of wind characteristics from 356-meter-high Shenzhen Meteorological Tower during a severe typhoon

  • He, Yinghou;Li, Qiusheng;Chan, Pakwai;Zhang, Li;Yang, Honglong;Li, Lei
    • Wind and Structures
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    • v.30 no.6
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    • pp.575-595
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    • 2020
  • The characteristics of winds associated with tropical cyclones are of great significance in many engineering fields. This paper presents an investigation of wind characteristics over a coastal urban terrain based on field measurements collected from multiple cup anemometers and ultrasonic anemometers equipped at 13 height levels on a 356-m-high meteorological tower in Shenzhen during severe Typhoon Hato. Several wind quantities, including wind spectrum, gust factor, turbulence intensity and length scale as well as wind profile, are presented and discussed. Specifically, the probability distributions of fluctuating wind speeds are analyzed in connection with the normal distribution and the generalized extreme value distribution. The von Karman spectral model is found to be suitable to depict the energy distributions of three-dimensionally fluctuating winds. Gust factors, turbulence intensity and length scale are determined and discussed. Moreover, this paper presents the wind profiles measured during the typhoon, and a comparative study of the vertical distribution of wind speeds from the field measurements and existing empirical models is performed. The influences of the topography features and wind speeds on the wind profiles were investigated based on the field-measured wind records. In general, the empirical models can provide reasonable predictions for the measured wind speed profiles over a typical coastal urban area during a severe typhoon.

Improvement of MFL sensing-based damage detection and quantification for steel bar NDE

  • Kim, Ju-Won;Park, Minsu;Kim, Junkyeong;Park, Seunghee
    • Smart Structures and Systems
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    • v.22 no.2
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    • pp.239-247
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    • 2018
  • A magnetic flux leakage (MFL) method was applied to detect and quantify defects in a steel bar. A multi-channel MFL sensor head was fabricated using Hall sensors and magnetization yokes with permanent magnets. The MFL sensor head scanned a damaged specimen with five levels of defects to measure the magnetic flux density. A series of signal processing procedures, including an enveloping process based on the Hilbert transform, was performed to clarify the flux leakage signal. The objective damage detection of the enveloped signals was then analyzed by comparing them to a threshold value. To quantitatively analyze the MFL signal according to the damage level, five kinds of damage indices based on the relationship between the enveloped MFL signal and the threshold value were applied. Using the proposed damage indices and the general damage index for the MFL method, the detected MFL signals were quantified and analyzed relative to the magnitude of the damage increase.

Suggestion of Probable Rainfall Intensity Formula Considering the Pattern Change of Maximum Rainfall at Incheon City (최대강우 패턴 변화를 고려한 인천지방 확률강우강도식의 제안)

  • Han Man-Shin;Choi Gye-Woon;Chung Yeun-Jung;Ahn Kyung-Soo
    • Journal of Korea Water Resources Association
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    • v.39 no.6 s.167
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    • pp.521-531
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    • 2006
  • The formula was proposed through the examination of probability rainfall intensity formula used in Incheon based upon recent occurrences of heavy rain and extraordinary storms. Random-time maximum annual rainfalls were estimated for durations from ten minutes to twenty-four hours from the data by Korea Meteorological Administration. Eleven types of probability distribution are considered to estimate probable rainfall depths for different storm durations at Incheon city. Three goodness-of-fit tests including Chi-square, Kolmogorov-Smirmov and framer Von Misses were used to analyze the tendency of recent rainfall. Considering maximum rainfall occurred, General Extreme Value(GEV) distribution was chosen as the appropriate probability distribution. Five types of probability rainfall formulas including Talbot type, Sherman type, Japanese type, unified type I and unified type II are considered to determine the best type for rainfall intensity at Incheon. The formula was determined considering the time of concentration of sewer system and river at Incheon city. Unified type I was chosen for its accuracy and was proposed to represent rainfall intensity of Incheon district.

Application of a large-scale ensemble climate simulation database for estimating the extreme rainfall (극한강우량 산정을 위한 대규모 기후 앙상블 모의자료의 적용)

  • Kim, Youngkyu;Son, Minwoo
    • Journal of Korea Water Resources Association
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    • v.55 no.3
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    • pp.177-189
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    • 2022
  • The purpose of this study is to apply the d4PDF (Data for Policy Decision Making for Future Change) constructed from a large-scale ensemble climate simulation to estimate the probable rainfall with low frequency and high intensity. In addition, this study analyzes the uncertainty caused by the application of the frequency analysis by comparing the probable rainfall estimated using the d4PDF with that estimated using the observed data and frequency analysis at Geunsam, Imsil, Jeonju, and Jangsu stations. The d4PDF data consists of a total of 50 ensembles, and one ensemble provides climate and weather data for 60 years such as rainfall and temperature. Thus, it was possible to collect 3,000 annual maximum daily rainfall for each station. By using these characteristics, this study does not apply the frequency analysis for estimating the probability rainfall, and we estimated the probability rainfall with a return period of 10 to 1000 years by distributing 3,000 rainfall by the magnitude based on a non-parametric approach. Then, the estimated probability rainfall using d4PDF was compared with those estimated using the Gumbel or GEV distribution and the observed rainfall, and the deviation between two probability rainfall was estimated. As a result, this deviation increased as the difference between the return period and the observation period increased. Meanwhile, the d4PDF reasonably suggested the probability rainfall with a low frequency and high intensity by minimizing the uncertainty occurred by applying the frequency analysis and the observed data with the short data period.