• Title/Summary/Keyword: boundary kernel density function

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Frequency Analysis of Meteorologic Drought Indices using Boundary Kernel Density Function (경계핵밀도함수를 이용한 기상학적 가뭄지수의 빈도해석)

  • Oh, Tae Suk;Moon, Young-Il;Kim, Seong Sil;Park, Gu Sun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.2B
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    • pp.87-98
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    • 2011
  • Recently, occurrence frequency of extreme events like flood and drought is increasing due to climate change by global warming. Especially, a drought is more severer than other hydrologic disasters because it causes continuous damage through long period. But, ironically, it is difficult to recognize the importance and seriousness of droughts because droughts occur for a long stretch of time unlike flood. So as to analyze occurrence of droughts and prepare a countermeasure, this study analyzed a meteorologic drought among many kinds of drought that it is closely related with precipitation. Palmer Drought Severity Index, Standard Precipitation and Effective Drought Index are computed using precipitation and temperature material observed by Korean Meteorological Administration. With the result of comparative analysis of computed drought indices, Effective Drought Index is selected to execute frequency analysis because it is accordant to past droughts and has advantage to compute daily indices. A Frequency analysis of Effective Drought Index was executed using boundary kernel density function. In the result of analysis, occurrence periods of spring showed about between 10 year and 20 year, it implies that droughts of spring are more frequent than other seasons. And severity and occurrence period of droughts varied in different regions as occurrence periods of the Youngnam region and the southern coast of Korea are relatively shorter than other regions.

Drought Assessment of the Korean Peninsula through Drought Frequency Analysis (가뭄빈도해석을 통한 한반도의 가뭄 평가)

  • Kim, Seong-Sil;Moon, Young-Il;Park, Gu-Soon;Oh, Tae-Suk
    • Proceedings of the Korea Water Resources Association Conference
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    • 2011.05a
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    • pp.32-36
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    • 2011
  • 가뭄은 홍수와 같이 단기간에 피해를 발생시키는 것이 아니라 장기간에 걸쳐 서서히 진행되므로 그 심각성을 인식하기 어렵고 국가 차원의 대책 또한 미비한 실정이다. 따라서 본 연구에서는 가뭄의 발생특성을 파악하기 위해 기상학적 가뭄지수를 산정하여 가뭄빈도해석을 실시하였다. 빈도해석방법은 weibull분포를 이용한 매개변수적 방법과 경계핵밀도함수(Boundary Kernel Density Function)를 이용한 비매개변수적 방법을 병행하여 재현기간별 가뭄심도를 산정하였다.

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A Study on Target Standardized Precipitation Index in Korea (한반도 목표 표준강수지수(SPI) 산정에 관한 연구)

  • Kim, Min-Seok;Moon, Young-Il
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.4
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    • pp.1117-1123
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    • 2014
  • Water is a necessary condition of plants, animals and human. The state of the water shortage, that drought is globally one of the most feared disasters. This study was calculated target standardized precipitation index with unit of region for judgment and preparation of drought in consideration of the regional characteristics. First of all, Standardized Precipitation Index (3) were calculated by monthly rainfall data from rainfall data more than 30 years of 88 stations. Parametric frequency and nonparametric frequency using boundary kernel density function were analysed using annual minimum data that were extracted from calculated SPI (3). Also, Target return period sets up 30 year and target SPI analysed unit of region using thiessen by result of nonparametric frequency. Analyzed result, Drought was entirely different from severity and frequency by region. This study results will contribute to a national water resources plan and disaster prevention measures with data foundation for judgment and preparation of drought in korea.

Classification of Music Data using Fuzzy c-Means with Divergence Kernel (분산커널 기반의 퍼지 c-평균을 이용한 음악 데이터의 장르 분류)

  • Park, Dong-Chul
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.3
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    • pp.1-7
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    • 2009
  • An approach for the classification of music genres using a Fuzzy c-Means(FcM) with divergence-based kernel is proposed and presented in this paper. The proposed model utilizes the mean and covariance information of feature vectors extracted from music data and modelled by Gaussian Probability Density Function (GPDF). Furthermore, since the classifier utilizes a kernel method that can convert a complicated nonlinear classification boundary to a simpler linear one, he classifier can improve its classification accuracy over conventional algorithms. Experiments and results on collected music data sets demonstrate hat the proposed classification scheme outperforms conventional algorithms including FcM and SOM 17.73%-21.84% on average in terms of classification accuracy.

Flow Simulation of High Flow Concrete using Incompressible Smoothed Particle Hydrodynamics (ISPH) Method (ISPH 기법을 이용한 고유동 콘크리트의 유동 해석)

  • Kim, Sang-Sin;Chung, Chul-Woo;Lee, Chang-Joon
    • Journal of the Korea Institute of Building Construction
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    • v.19 no.1
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    • pp.39-46
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    • 2019
  • A three-dimensional flow simulation model for high flow concrete was developed using Incompressible Smoothed Particle Hydrodynamics (ISPH), which can solved Navier-Stokes equation with the assumption of a fluid to be incompressible. For the simulation, a computer program code for ISPH was implemented with MATALB programming code. A piecewise cubic spline function was used for the kernel function of ISPH. Projetion method was used to calculate the velocity and pressure of particles as a function of time. Fixed ghost particle was used for wall boundary condition. Free surface boundaries were determined by using virtual density of particles. In order to validate the model and the code, the simulation results of slump flow test, $T_{500}$ test and L-box test were compared with experimental ones. The simulation results were well matched with the experimental results. The simulation described successfully the characteristics of the flow phenomenon according to the change of the viscosity and yield stress of high flow concrete.