• Title/Summary/Keyword: representative probability distribution

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A Derivation of Rainfall Intensity-Duration-Frequency Relationship for the Design of Urban Drainage System in Korea (우리나라 도시배수시스템 설계를 위한 확률강우강도식의 유도)

  • Lee, Jae-Jun;Lee, Jeong-Sik
    • Journal of Korea Water Resources Association
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    • v.32 no.4
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    • pp.403-415
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    • 1999
  • This study is to derive the rainfall intensity formula based on the representative probability distribution in Korea. The 11 probability distributions which has been widely used in hydrologic frequency analysis are applied to the annual maximum rainfall. The parameters of each probability distribution are estimated by method of moments, maximum likelihood method and method of probability weighted moments. Four tests such as $x^2$-test, Kolmogorv-Smirnov test, difference test and modified difference test are used to determine the goodness of fit of the distributions. The homogeneous tests (Mann-Whitney U test, Kruskal-Wallis one-way analysis of variance of nonparametric test) are applied to find the stations with rainfall homogeneity. The results of homogeneous tests show that there is no representative appropriate distribution for the whole duration in Korea. The whole region could be divided into five zones for 12-durations. The representative probability distribution of each divided zone for 12-durations was determined. The GEV distribution for I,II,V zones and the 3-parameter Weibull distribution for III,IV zones were determined as the representative probability distribution. The rainfall were obtained from representative probability distribution for the selected return periods. Rainfall intensity formula was determined by linearization technique for the rainfall.

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A Derivation of Regional Representative Intensity-Duration-Frequency Relationship Using Multivariate Analysis (다변량 분석을 이용한 권역별 대표확률강우강도식의 유도)

  • Lee, Jung-Sik;Cho, Seong-Geun;Jang, Jin-Uk
    • Journal of the Korean Society of Hazard Mitigation
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    • v.7 no.2 s.25
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    • pp.13-24
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    • 2007
  • This study is to derive the rainfall intensity formula based on the representative probability distribution using multivariate analysis in Korea. The annual maximum rainfall data at 57 stations having more than 30years long records were used for 12 durations(10min, 1, 2, 3, 4, 5, 6, 8, 10, 12, 18, 24hr). 50 rainfall characteristics elements are analyzed from the collected data. The widely used 14 probability distributions are applied to the basic data in hydrologic frequency analysis. The homogeneous tests(principal component and cluster analysis) are applied to find the rainfall homogeneity. The results of this study are as followings; (1) The homogeneous test shows that there is no appropriate representative distribution for the whole duration in Korea. But hydrological homogeneous regions of point rainfall could be divided by 5 regions. (2) The GEV distribution for zones I, III, IV, V and the Gumbel distribution for zone II are determined as the representative probability distribution. (3) Comparative analysis of the results shows that the probable rainfalls of representative zones are different from those of existing researches. (4) Rainfall intensity formulas are determined on the basis of the linearization technique for the probable rainfall.

Vessel traffic geometric probability approaches with AIS data in active shipping lane for subsea pipeline quantitative risk assessment against third-party impact

  • Tanujaya, Vincent Alvin;Tawekal, Ricky Lukman;Ilman, Eko Charnius
    • Ocean Systems Engineering
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    • v.12 no.3
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    • pp.267-284
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    • 2022
  • A subsea pipeline designed across active shipping lane prones to failure against external interferences such as anchorage activities, hence risk assessment is essential. It requires quantifying the geometric probability derived from ship traffic distribution based on Automatic Identification System (AIS) data. The actual probability density function from historical vessel traffic data is ideal, as for rapid assessment, conceptual study, when the AIS data is scarce or when the local vessels traffic are not utilised with AIS. Recommended practices suggest the probability distribution is assumed as a single peak Gaussian. This study compares several fitted Gaussian distributions and Monte Carlo simulation based on actual ship traffic data in main ship direction in an active shipping lane across a subsea pipeline. The results shows that a Gaussian distribution with five peaks is required to represent the ship traffic data, providing an error of 0.23%, while a single peak Gaussian distribution and the Monte Carlo simulation with one hundred million realisation provide an error of 1.32% and 0.79% respectively. Thus, it can be concluded that the multi-peak Gaussian distribution can represent the actual ship traffic distribution in the main direction, but it is less representative for ship traffic distribution in other direction. The geometric probability is utilised in a quantitative risk assessment (QRA) for subsea pipeline against vessel anchor dropping and dragging and vessel sinking.

A Study on Developing the Optimal Sizing System for Ready-to-wear - Based on Elementary School Girls - (기성복의 최적 사이즈 시스템 개발을 위한 연구 - 학령기 여아를 중심으로 -)

  • Kim Ran-do;Lee Sang-youl;Kim Seon-young;Nam Yun-ja
    • Journal of the Korean Society of Clothing and Textiles
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    • v.29 no.8 s.145
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    • pp.1102-1113
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    • 2005
  • The propose of this study is to develop the optimal sizing system of ready-to-wear f3r elementary school girls using a newly invented statistical technique. The body measurements was classified by the method that equalizes the distribution of the subjects using the probability density function, to theoretically systemize a method to determine a size range of ready-to-wear for elementary school girls between 6 to 12 years old. The statistical method were 1) The total of 11 height groups, which size interval from one another is 6 cm that is an average height gap between each age. 2) In order to determine an approximate figure (m ${\times}$ n) to establish the appropriate sizes far each height group that fit to the combinations of bust and hip girth, which based on their means and standard deviations on the probability density curve to produce the standard normal distribution. 3) m and n were aligned by 4cm -the grading increments used for patterns making- and determined the size ranges by confirming the approximate figures of m and n. 4) The representative values were determined by an area ratio calculated by dividing the area determined from the range of bust and hip girth with the representative value. Considering the characteristics of subjects' distribution, the area ratios was used. 5) Weight was calculated by seeking a growth exponent for each age and multiplying it by the number of girls that fit to each size range. As sections that show the highest weight are more likely sought by the consumers, these sections were determined as the optimal size standards. 6) This optimal sizing system consists of sizes determined by the optimal size standards and its sizes are marked with height, bust and hip girth.

Evaluation of RVE Suitability Based on Exponential Curve Fitting of a Probability Distribution Function (확률 분포 함수의 지수 곡선 접합을 이용한 RVE 적합성 평가)

  • Chung, Sang-Yeop;Yun, Tae Sup;Han, Tong-Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.5A
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    • pp.425-431
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    • 2010
  • The phase distribution in a multi-phase material strongly affects its material properties. Therefore, a proper method to describe the phase distribution of a material is needed. In this research, probability distribution functions, two-point correlation and lineal-path functions, are used to represent the probabilistic phase distributions of a material. The probability distribution function is calculated using a numerical method and is described as an analytical form via exponential curve fitting with three parameters. Application of analytical form of probability distribution function is investigated using two-phase polycrystalline solids and soil samples. It is confirmed that the probability distribution functions can be represented as an exponential form using curve fitting which helps identifying the applicability of a representative volume element(RVE).

Development of Weigh Calculation Method for Pavement Roughness Index Considering Vehicle Wandering Distribution (원더링 분포를 고려한 도로포장 평탄성 지수의 가중치 산정기법 개발)

  • Lee, Jaehoon;Sohn, Ducksu;Park, Jejin;Cho, Yoonho
    • International Journal of Highway Engineering
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    • v.19 no.5
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    • pp.89-96
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    • 2017
  • PURPOSES: This study aims to develop a rational procedure for estimating the pavement roughness index considering vehicle wandering. METHODS : The location analysis of the passing vehicle in the lane was performed by approximately 1.2 million vehicles for verification of the wandering distribution. According to verification result, the distribution follows the normal distribution pattern. The probability density function was estimated using each lane's wandering distribution model. Then the procedure for applying a weighted value into the lane profile was conducted using this function. RESULTS : The modified index, MRIw, with consideration towards applying the wandering weighted value application was computed then compared with MRI. It was found that the Coefficient of Variation for distribution of lateral roughness index in the lane was high in the case of a large difference between each index (i.e., MRIw and MRI) observed. CONCLUSIONS : This result confirms that the new procedure with consideration of the weight factor can successfully improve the lane representative characteristics of the roughness index.

Comparison of Wind Energy Density Distribution Using Meteorological Data and the Weibull Parameters (기상데이터와 웨이블 파라메타를 이용한 풍력에너지밀도분포 비교)

  • Hwang, Jee-Wook;You, Ki-Pyo;Kim, Han-Young
    • Journal of the Korean Solar Energy Society
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    • v.30 no.2
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    • pp.54-64
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    • 2010
  • Interest in new and renewable energies like solar energy and wind energy is increasing throughout the world due to the rapidly expanding energy consumption and environmental reasons. An essential requirement for wind force power generation is estimating the size of wind energy accurately. Wind energy is estimated usually using meteorological data or field measurement. This study attempted to estimate wind energy density using meteorological data on daily mean wind speed and the Weibull parameters in Seoul, a representative inland city where over 60% of 15 story or higher apartments in Korea are situated, and Busan, Incheon, Ulsan and Jeju that are major coastal cities in Korea. According to the results of analysis, the monthly mean probability density distribution based on the daily mean wind speed agreed well with the monthly mean probability density distribution based on the Weibull parameters. This finding suggests that the Weibull parameters, which is highly applicable and convenient, can be utilized to estimate the wind energy density distribution of each area. Another finding was that wind energy density was higher in coastal cities Busan and Incheon than in inland city Seoul.

Application of Jackknife Method for Determination of Representative Probability Distribution of Annual Maximum Rainfall (연최대강우량의 대표확률분포형 결정을 위한 Jackknife기법의 적용)

  • Lee, Jae-Joon;Lee, Sang-Won;Kwak, Chang-Jae
    • Journal of Korea Water Resources Association
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    • v.42 no.10
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    • pp.857-866
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    • 2009
  • In this study, basic data is consisted annual maximum rainfall at 56 stations that has the rainfall records more than 30years in Korea. The 14 probability distributions which has been widely used in hydrologic frequency analysis are applied to the basic data. The method of moments, method of maximum likelihood and probability weighted moments method are used to estimate the parameters. And 4-tests (chi-square test, Kolmogorov-Smirnov test, Cramer von Mises test, probability plot correlation coefficient (PPCC) test) are used to determine the goodness of fit of probability distributions. This study emphasizes the necessity for considering the variability of the estimate of T-year event in hydrologic frequency analysis and proposes a framework for evaluating probability distribution models. The variability (or estimation error) of T-year event is used as a criterion for model evaluation as well as three goodness of fit criteria (SLSC, MLL, and AIC) in the framework. The Jackknife method plays a important role in estimating the variability. For the annual maxima of rainfall at 56 stations, the Gumble distribution is regarded as the best one among probability distribution models with two or three parameters.