• Title/Summary/Keyword: L-moment estimation

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Estimation of Probability Precipitation by Regional Frequency Analysis using Cluster analysis and Variable Kernel Density Function (군집분석과 변동핵밀도함수를 이용한 지역빈도해석의 확률강우량 산정)

  • Oh, Tae Suk;Moon, Young-Il;Oh, Keun-Taek
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.2B
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    • pp.225-236
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    • 2008
  • The techniques to calculate the probability precipitation for the design of hydrological projects can be determined by the point frequency analysis and the regional frequency analysis. Probability precipitation usually calculated by point frequency analysis using rainfall data that is observed in rainfall observatory which is situated in the basin. Therefore, Probability precipitation through point frequency analysis need observed rainfall data for enough periods. But, lacking precipitation data can be calculated to wrong parameters. Consequently, the regional frequency analysis can supplement the lacking precipitation data. Therefore, the regional frequency analysis has weaknesses compared to point frequency analysis because of suppositions about probability distributions. In this paper, rainfall observatory in Korea did grouping by cluster analysis using position of timely precipitation observatory and characteristic time rainfall. Discordancy and heterogeneity measures verified the grouping precipitation observatory by the cluster analysis. So, there divided rainfall observatory in Korea to 6 areas, and the regional frequency analysis applies index-flood techniques and L-moment techniques. Also, the probability precipitation was calculated by the regional frequency analysis using variable kernel density function. At the results, the regional frequency analysis of the variable kernel function can utilize for decision difficulty of suitable probability distribution in other methods.

The Study on Application of Regional Frequency Analysis using Kernel Density Function (핵밀도 함수를 이용한 지역빈도해석의 적용에 관한 연구)

  • Oh, Tae-Suk;Kim, Jong-Suk;Moon, Young-Il;Yoo, Seung-Yeon
    • Journal of Korea Water Resources Association
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    • v.39 no.10 s.171
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    • pp.891-904
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    • 2006
  • The estimation of the probability precipitation is essential for the design of hydrologic projects. The techniques to calculate the probability precipitation can be determined by the point frequency analysis and the regional frequency analysis. The regional frequency analysis includes index-flood technique and L-moment technique. In the regional frequency analysis, even if the rainfall data passed homogeneity, suitable distributions can be different at each point. However, the regional frequency analysis can supplement the lacking precipitation data. Therefore, the regional frequency analysis has weaknesses compared to parametric point frequency analysis because of suppositions about probability distributions. Therefore, this paper applies kernel density function to precipitation data so that homogeneity is defined. In this paper, The data from 16 rainfall observatories were collected and managed by the Korea Meteorological Administration to achieve the point frequency analysis and the regional frequency analysis. The point frequency analysis applies parametric technique and nonparametric technique, and the regional frequency analysis applies index-flood techniques and L-moment techniques. Also, the probability precipitation was calculated by the regional frequency analysis using variable kernel density function.

Estimates of Regional Flood Frequency in Korea (우리나라의 빈도홍수량의 추정)

  • Kim, Nam-Won;Won, Yoo-Seung
    • Journal of Korea Water Resources Association
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    • v.37 no.12
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    • pp.1019-1032
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    • 2004
  • Flood frequency estimate is an essential index for determining the scale of small and middle hydraulic structure. However, this flood quantity could not be estimated directly for practical design purpose due to the lack of available flood data, and indirect method like design rainfall-runoff method have been used for the estimation of design flood. To give the good explain for design flood estimates, regional flood frequency analysis was performed by flood index method in this study. First, annual maximum series were constructed by using the collected data which covers from Japanese imperialism period to 1999. Wakeby distribution recommended by WMO(1989) was used for regional flood frequency analysis and L-moment method by Hosking (1990) was used for parameter estimation. For the homogeneity of region, the discordance and heterogeneity test by Hosking and Wallis(1993) was carried for 4 major watersheds in Korea. Physical independent variable correlated with index flood was watershed area. The relationship between specific discharge and watershed area showed a type of power function, i.e. the specific discharge decreases as watershed area increases. So flood quantity according to watershed area and return period was presented for each watershed(Han rivet, Nakdong river, Geum river and Youngsan/Seomjin river) by using this relation type. This result was also compared with the result of point frequency analysis and its regionalization. It was shown that the dam construction couldn't largely affect the variation of peak flood. The property of this study was also examined by comparison with previous studies.

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

  • 맹승진;이순혁
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.45 no.1
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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.

Estimation of Design Rainfall Considering the Change of the Number of Years for Observed Data (관측년수변화를 고려한 설계강우량 산정)

  • Ryoo, Kyong-Sik;Lee, Soon-Hyuk;Hwang, Man-Ha;Lee, Sang-Jin
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2005.10a
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    • pp.284-287
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    • 2005
  • The objective of this study is to check into variation trends of design rainfall according to change of the number of years for observed data. To make comparative study of the relation between design rainfall and recorded year, this study was used maximum rainfall for 24-hr consecutive duration at Gangneung, Seoul, Incheon, Chupungnyeong, Pohang, Daegu, Jeonju, Ulsan, Gwangju, Busan, Mokpo and Yeosu rainfall stations. The tests for Independence, Homogeneity and detection of outliers were used Wald-Wolfowitz's test, Mann-Whitney's test and Grubbs and Beck test respectively. To select appopriate distribution, the distribution of genaralized pareto(GPA), generalized extreme value(GEV), generalized logistic(GLO), lognormal and pearson type 3 distribution is judged by L-moment ratio diagram and Kolmogorov-Smirnov (K-S) test. Design rainfall was estimated by at-site frequency analysis using L-moments and Generalized extreme value(GEV) distribution according to change of the number of years for observed data. Through the comparative analysis for design rainfall induced by L-moments and GEV distribution, relationship between design rainfall and recorded year is provided.

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Estimation of Stream Water Quality Changes Brought by a New Town Development (신도시 개발 후 도시하천의 장래수질 평가)

  • Park, Ji-Young;Lim, Hyun-Man;Yoon, Young-Han;Jung, Jin-Hong;Kim, Weon-Jae
    • Journal of Korean Society of Environmental Engineers
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    • v.36 no.1
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    • pp.58-66
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    • 2014
  • Water pollution problems of urban rivers due to the urbanization and industrialization have been the subject of public attention. In particular, considering the fact that the characteristics of water cycle of each basin change dramatically through the development of new towns, a large number of concerns about future water quality have been raised. However, reasonable measures to predict future water quality quantitatively have not been presented by this moment. In this study, by the linkage of annual unit load generation based on long-term monitoring results of the ministry of environment (MOE) to a semi-distributed rainfall runoff model, SWMM (Storm Water Management Model), we proposed a new methodology to estimate future water quality macroscopically and testified it to verify its applicability for the estimation of future water quality of a small watershed at G new town. As a result of the estimation using Y-EMC (Yearly based Event Mean Concentration), future water quality were simulated as BOD 18.7, T-N 16.1 and T-P 0.85 mg/L respectively which could not achieve the grade III of domestic river life guidance and these criteria could be satisfied by the reduction of domestic wastewater discharge load by over 80%. The results of this study are shown to be utilized for one of basic tools to estimate and manage water quality of urban rivers in the course of new town developments.

Comparative Evaluation of Two Analytical Models for Microwave Scattering from Deciduous Leaves

  • Oh, Yi-Sok
    • Korean Journal of Remote Sensing
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    • v.20 no.1
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    • pp.39-46
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    • 2004
  • The generalized Rayleigh-Gans (GRG) approximation is usually used to compute the scattering amplitudes of leaves smaller or comparable to a wavelength, while the physical optics (PO) approach with the resistive sheet approximation is commonly used for leaves larger or comparable to the wavelength. In this paper, the scattering amplitudes of an elliptical leaf are computed using those theoretical scattering models (GRG and PO) at different frequencies. The accuracies of the analytical models for microwave scattering from deciduous leaves are investigated by comparison with the precise estimation by the method of moment (MoM). It was found that both the PO approach and the GRG approximation can be used alternatively for computing the scattering matrices of natural deciduous leaves at P-, L-, C- and X-band frequencies.

Novel Optimizer AdamW+ implementation in LSTM Model for DGA Detection

  • Awais Javed;Adnan Rashdi;Imran Rashid;Faisal Amir
    • International Journal of Computer Science & Network Security
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    • v.23 no.11
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    • pp.133-141
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    • 2023
  • This work take deeper analysis of Adaptive Moment Estimation (Adam) and Adam with Weight Decay (AdamW) implementation in real world text classification problem (DGA Malware Detection). AdamW is introduced by decoupling weight decay from L2 regularization and implemented as improved optimizer. This work introduces a novel implementation of AdamW variant as AdamW+ by further simplifying weight decay implementation in AdamW. DGA malware detection LSTM models results for Adam, AdamW and AdamW+ are evaluated on various DGA families/ groups as multiclass text classification. Proposed AdamW+ optimizer results has shown improvement in all standard performance metrics over Adam and AdamW. Analysis of outcome has shown that novel optimizer has outperformed both Adam and AdamW text classification based problems.

Regional Frequency Analysis for Rainfall Under Climate Change (기후변화를 고려한 일강우량의 지역빈도해석)

  • Song, Chang Woo;Kim, Yon Soo;Kang, Na Rae;Lee, Dong Ryul;Kim, Hung Soo
    • Journal of Wetlands Research
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    • v.15 no.1
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    • pp.125-137
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    • 2013
  • Global warming and climate change have influence on abnormal weather pattern and the rainstorm has a localized and intensive tendency in Korea. IPCC(2007) also reported the rainstorm and typhoon will be more and more stronger due to temperature increase during the 21st century. Flood Estimation Handbook(Institute of Hydrology, 1999) published in United Kingdom, in the case that the data period is shorter than return period, recommends the regional frequency analysis rather than point frequency analysis. This study uses Regional Climate Model(RCM) of Korea Meteorological Administration(KMA) for obtaining the rainfall and for performing the regional frequency analysis. We used the rainfall data from 58 stations managed by KMA and used L-moment algorithm suggested by Hosking and wallis(1993) for the regional frequency analysis considering the climate change. As the results, in most stations, the rainfall amounts in frequencies have an increasing tendency except for some stations. According to the A1B scenario, design rainfall is increased by 7~10% compared with the reference period(1970-2010).

The Determination of Probability Distributions of Annual, Seasonal and Monthly Precipitation in Korea (우리나라의 연 강수량, 계절 강수량 및 월 강수량의 확률분포형 결정)

  • Kim, Dong-Yeob;Lee, Sang-Ho;Hong, Young-Joo;Lee, Eun-Jai;Im, Sang-Jun
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.12 no.2
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    • pp.83-94
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    • 2010
  • The objective of this study was to determine the best probability distributions of annual, seasonal and monthly precipitation in Korea. Data observed at 32 stations in Korea were analyzed using the L-moment ratio diagram and the average weighted distance (AWD) to identify the best probability distributions of each precipitation. The probability distribution was best represented by 3-parameter Weibull distribution (W3) for the annual precipitation, 3-parameter lognormal distribution (LN3) for spring and autumn seasons, and generalized extreme value distribution (GEV) for summer and winter seasons. The best probability distribution models for monthly precipitation were LN3 for January, W3 for February and July, 2-parameter Weibull distribution (W2) for March, generalized Pareto distribution (GPA) for April, September, October and November, GEV for May and June, and log-Pearson type III (LP3) for August and December. However, from the goodness-of-fit test for the best probability distributions of the best fit, GPA for April, September, October and November, and LN3 for January showed considerably high reject rates due to computational errors in estimation of the probability distribution parameters and relatively higher AWD values. Meanwhile, analyses using data from 55 stations including additional 23 stations indicated insignificant differences to those using original data. Further studies using more long-term data are needed to identify more optimal probability distributions for each precipitation.