• 제목/요약/키워드: relative root mean square

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Wakeby 분포모형의 확률가중모멘트기법에 의한 설계홍수량 유도(수공) (Derivation of Design Floods by the Probability Weighted Moments in the Wakeby Distribution)

  • 송기헌;이순혁;박종화;맹승진;류경식;지호근
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2000년도 학술발표회 발표논문집
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    • pp.352-358
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    • 2000
  • The objective of this study is to derive optimal design floods by the Wakeby distribution using the probability weighted moments. parameters for the Wakeby distribution were estimated by the probability weighted moments for the annual flood flows of the applied watersheds. Design floods obtained by the Wakeby and GEV distributions were compared by the relative mean errors, relative absolute errors and root mean square errors. In general, it has shown that the design floods by the Wakeby distribution using the methods of the probability weighted moments are closer to those of the observed data in comparison with those obtained by the GEV distribution.

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Weibull -3 및 Wakeby 분포의 L-모멘크법에 의한 설계갈수량 비교분석 (Comparative Analysis of Design Drought Flow by L-Moment in the Weibull-3 and Wakeby distributions)

  • 이순혁;박종화;맹승진;류경식;지호근
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
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    • pp.531-536
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    • 1999
  • This study was carried out to derive optimal design drought flows by the Weibull-3 and Wakeby distributions for the annual drought flows series at seven watersheds along Han, Nagdong, Geum, Yeongsan and Seomjin river systems. L-coefficient of variation , L-skewness and L-kurtosis were calculated by the L-moment ratio respectivley. Parameters were estimated by the Methods o fL-Moments with continuous duration. Design drought flows obtained by Methods of L-Moments using Weibull plotting positions formula in the Weibull-3 and Wakeby distributions were compared by the Relative Mean Errors(RME), Relative Absolute Errors (RAE) and Root Mean Square Errors(RMSE). It has shown that design drought flows by the Wakeby distribution using method of L-moments are much closer to those of the observed data in comparison with those obtained by the Weibull-3 distribution using method of L-moments.

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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.

Log-Pearson Type III 분포형에 의한 강우의 점빈도 및 지역빈도 비교분석 (Comparative Analysis of regional and at-site frequency for the design rainfall by Log-Pearson Type III Distribution)

  • 류경식;이순혁;맹승진;송기헌;김기창
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2003년도 학술발표논문집
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    • pp.475-478
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    • 2003
  • This study was conducted to compare the design rainfall derived by the at-site and regional frequency analysis based on the regionalization of the precipitation. The regional and at-site design rainfalls were calculated by Log-Pearson type III distribution using Indirect Methods of Moments(WRC). 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 between design rainfalls resulted from observed and simulated data using the regional and at-site analysis. It was shown that the regional analysis procedure can substantially reduce the RRMSE, RBIAS in comparison with those of at-site analysis. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.

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지점 및 지역빈도분석에 의한 설계강우량의 추정 (Estimation of Design Rainfall derived by At-site and Regional Frequency Analysis)

  • 류경식;이순혁;맹승진
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2004년도 학술발표회
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    • pp.318-322
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    • 2004
  • This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation. For the estimation of the regional design rain(all, classification of the climatologically and geographically homogeneous regions should be preceded preferentially The optimal regionalization of the precipitation data were classified by the above mentioned conditions for all over the regions except Jeju and Ulleung islands in Korea. Relative root mean square error(RRMSE), relative bias(RBIAS) and relative reduction(RR) in RRMSE for the design rainfall were computed and compared between the regional and at-site frequency analysis. Consequently, optimal design rainfalls following the classified regions and consecutive durations were derived by the regional frequency analysis using GEV distribution which was identified to be more optimal one than the other applied distributions.

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RCP4.5 기후변화 시나리오와 인공신경망을 이용한 우리나라 확률강우량의 변화 (The change of rainfall quantiles calculated with artificial neural network model from RCP4.5 climate change scenario)

  • 이주형;허준행;김기주;김영오
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.130-130
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    • 2022
  • 기후변화로 인한 기상이변 현상으로 폭우와 홍수 등 수문학적 극치 사상의 출현 빈도가 잦아지고 있다. 따라서 이러한 기상이변 현상에 적응하기 위하여 보다 정확한 확률강우량 측정의 필요성이 증가하고 있다. 대장 지점의 미래 확률강우량 계산을 위해선 기후변화 시나리오의 비정상성을 고려해야 한다. 본 연구는 비정상적인 미래 기후에서 확률강우량이 어떻게 변화하는지 측정하는 것을 목표로 한다. Representative Concentration Pathway (RCP4.5)에 따른 우리나라의 확률강우량 계산에 인공신경망을 포함한 정상성, 비정상성 확률강우량 산정 모델들이 사용되었다. 지점빈도해석(AFA), 홍수지수법(IFM), 모분포홍수지수법(PIF), 인공신경망을 이용한 Quantile & Parameter regression technique(QRT & PRT)이 정상성 자료에 대해 확률강우량을 계산하는 모델로 사용되었으며, 비정상성 자료에 대해서는 비정상성 지점빈도해석(NS-AFA), 비정상성 홍수지수법(NS-IFM), 비정상성 모분포홍수지수법(NS-PIF), 인공신경망을 사용한 비정상성 Quantile & Parameter regression technique(NS-QRT & NS-PRT)이 사용되었다. Rescaled Akaike information criterion(rAIC)를 사용한 불확실성 분석과 적합도 검정을 통해서 generalized extreme value(GEV) 분포형 모델이 정상성 및 비정상성 확률강우량 산정에 가장 적합한 모델로 선정되었다. 이후, 관측자료가 GEV(0,0,0)을 따르고 시나리오 자료가 GEV(1,0,0)을 따르는 지점들을 선택하여 미래의 확률강우량 변화를 추정하였다. 각 빈도해석 모델들은 몬테카를로 시뮬레이션을 통해 bias, relative bias(Rbias), root mean square error(RMSE), relative root mean square error(RRMSE)를 바탕으로 측정하여 정확도를 계산하였으며 그 결과 QRT와 NS-QRT가 각각 정상성과 비정상성 자료로부터 가장 정확하게 확률강우량을 계산하였다. 본 연구를 통해 향후 기후변화의 영향으로 확률강우량이 증가할 것으로 예상되며, 비정상성을 고려한 빈도분석 또한 필요함을 제안하였다.

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확률 분포형의 극치 수문량 예측 능력 평가에 관한 연구 (A Study on the Estimation of Extreme Quantile of Probability Distribution)

  • 정진석;신홍준;안현준;허준행
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2017년도 학술발표회
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    • pp.399-400
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    • 2017
  • 홍수나 가뭄 등 극치 현상의 통계분석 및 빈도해석에 있어 극치분포형이 널리 사용되고 있으며, 이러한 극치분포형의 특성을 이해하기 위해서는 분포형의 오른쪽 꼬리(right tail) 부분 특성을 자세히 분석할 필요가 있다. 이에 따라 본 연구에서는 Monte Carlo 모의를 통하여 다양한 극치분포형의 오른쪽 꼬리 부분의 통계적 특성 및 그 예측 능력을 연구하였다. 극치분포형으로는 우리나라 확률수문량 산정에 널리 활용되고 있는 generalized extreme value (GEV), Gumbel, generalized logistic 분포를 사용하였으며, 매개변수 산정 방법으로는 확률가중모멘트법을 사용하였다. 모의실험의 모분포로는 수문빈도해석에서 많이 사용되는 GEV 분포를 사용하였고, 30년 이상 자료를 보유한 기상청 지점 자료의 왜곡도를 조사하여 모의실험에 사용되는 모집단의 왜곡도로 가정하여 표본 자료를 발생시켰다. 예측 능력의 평가는 재현기간 10~1000년의 확률수문량을 왜곡도계수를 고려한 GEV 도시위치공식을 이용하여 GEV 확률지에 도시하고, 평균제곱근오차(root mean square error), 편의(bias), 평균상대오차(mean relative difference), 평균절대상대오차(mean absolute relative difference)를 이용하여 최적 분포형을 선정함으로써 이루어진다. 또한 예측 능력 평가결과의 타당성 확인을 위해 극치분포형의 적합정도를 잘 나타낸다고 알려진 modified Anderson-Darling 방법의 검정결과와 비교하여 적절성을 확인하였다.

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모의 실험을 이용한 Right-tail quantiles의 극치 분포형 비교 평가에 관한 연구 (A Study on the Assessment of Right-tail Prediction Ability of Extreme Distributions using Simulation Experiment)

  • 정진석;김태림;송현근;허준행
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2016년도 학술발표회
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    • pp.158-158
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    • 2016
  • 본 연구에서는 극치 분포의 오른쪽 꼬리 부분 예측 시 안정적인 확률수문량 산정하는 확률분포형과 매개변수 추정 방법을 평가하기 위해 Monte Carlo 모의를 수행하였다. 수문자료의 빈도해석에 적합한 것으로 알려진 generalized extreme value (GEV), Gumbel (GUM), generalized logistic (GLO), gamma3 (GAM3), normal (NOR), log-normal3 (LN3) 총 6개의 확률분포형을 바탕으로 오른쪽 꼬리 부분의 확률수문량 추정 성능을 모의 실험을 통해 평가하고자 한다. 30년 이상 자료를 보유한 기상청 지점의 지속기간별 연최대값 자료를 분석한 결과를 바탕으로 모분포를 GEV분포로 선정하였으며 평균이 1.0, 표준편차 0.5, 왜곡도 계수는 0.5, 1.0, 2.0, 3.0, 4.0이 되도록 가정하였다. 또한 자료 길이에 따른 성능 평가를 위해 표본 크기 20, 50, 100, 150, 200개에 대해 분석을 수행하였다. 위와 같은 가정으로 총 25종류(왜곡도계수 5개 ${\times}$ 표본 크기 5개)의 발생된 모분포에 6가지의 확률분포형과 3가지의 매개변수 추정방법(모멘트법, 최우도법, 확률가중모멘트법)을 조합한 18가지의 모델을 비교 분석해보았다. 평가방법으로는 평균 제곱근 오차(Root Mean Square Error, RMSE), 편의(bias), 평균 상대오차(Mean Relative Difference, MRD), 평균 절대 상대오차(Mean Absolute Relative Difference, MARD)를 사용하여 적용 모델의 성능을 비교 분석하였다.

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Log-Pearson Type III 및 GEV분포모형에 의한 강우의 지점 및 지역빈도 비교분석 (Comparative Analysis of regional and at-site analysis for the design rainfall by Log-Pearson Type III and GEV Distribution)

  • 류경식;이순혁
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2003년도 학술발표논문집
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    • pp.443-446
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    • 2003
  • This study was conducted to draw design rainfall for the regional design rainfall derived by the optimal distribution and method of frequency analysis. The design rainfalls were calculated by the regional and at-site analysis for Log-Pearson type III and GEV distributions and were compared with Relative efficiency(RE) which is ratio of Relative root-mean-square error(RRMSE) by the regional and at-site analysis for Log-Pearson type III and GEV distributions. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis for GEV distribution and design rainfall maps were drawn by GIS techniques.

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Wavelet 변환을 이용한 배전 계통의 고 저항 사고 검출 알고리즘 (A High Impedance Fault Detection Algorithm Using Wavelet Transform)

  • 남순열;강용철;김성수;손진만;박종근;정성일;김광호;김일동
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1997년도 하계학술대회 논문집 D
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    • pp.975-978
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    • 1997
  • This Paper presents a high impedance fault (HIF) detection algorithm of distribution systems using wavelet transform. Two HIFs on dry soil and sandy soil were simulated on various load conditions in 22.9 kV distribution systems using EMTP, and the current wavelets were decomposed by wavelet transform. The current root mean square(rms) change, the index change rate and the relative amplitude change were used as the multi-criteria for a HIF detection. The index change rate and the relative amplitude were made using the wavelet coefficients.

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