• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.34-34
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• 2016

강우는 우리의 일상생활뿐만 아니라 각종 산업 활동 및 레저스포츠 등 많은 분야에 영향을 주는 중요한 기상 현상이다. 최근 들어 우리나라는 기후변화로 인해 과거 장마기간에 발생하였던 강우집중 현상이 장마기간 전후되어 발생하는 게릴라성 집중호우나 급작스런 이상강우의 형태를 보이고 있으며 그로 인해 홍수 예 경보체계 구축에 대한 중요성이 높아지고 있다. 하지만 우리나라의 경우 홍수 예 경보 체계 및 수공구조물 건설 등이 국가하천 위주로 운영되어 소하천에 대한 연구와 대책이 부족한 실정이다. 최근 이상호우에 의한 홍수피해 사례를 보면 지방하천 혹은 소하천으로부터 발생한 재산 및 인명피해가 크다는 것을 알 수 있으며 이를 관리하기 위한 시스템 구축이 절실한 상황이다. 특히 도시하천의 홍수방재를 위해서는 안정적이고 체계적인 도시하천관리가 필요한데 이를 위해서는 도시하천의 특성을 정확히 파악하는 것이 매우 중요하다. 국내에서 하천의 특성에 관한 연구동향을 살펴보면 대부분의 연구가 하천수질 관점에서 하천특성을 규명하는 목적으로 수행 되었고 홍수 방재를 위한 수문학적인 관점에서의 하천 특성을 도출하는 연구는 미비한 실정이다. 수문학적 관점에서의 하천특성은 유역면적, 도달시간, 형상계수 등 유역특성인자를 말하며 국내 하천에 적용 할 수 있는 대표 유역특성인자를 도출을 위해서는 통계학적인 방법이 필수적이다. 그 중에서도 요인분석, 주성분분석, 군집분석 등 다변량 통계기법을 이용한 분석 필요하다. 본 연구에서는 GIS분석과 지자체에서 제공하는 소하천정비기본계획을 통해 도시하천의 유역특성인자를 선정하고, 수문분야에서의 적용성이 높은 다변량 통계분석기법을 이용하여 우리나라를 대표할 수 있는 도시하천의 특성 및 권역별 도시하천의 특성을 도출하였다. 또한 대조군에 적용하여 도출된 특성의 적정성을 평가하였고 이를 통해 도시하천 관리에 이용될 수 있는 도시하천의 특성을 제시하고자 한다.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.475-485
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• 2007

In this work we measured and analyzed the subjective opinions of consumers towards the sound quality of car audios through a questionnaire. First of all, we chose eight controllable factors which had been known to affect the quality of reproduced sound. An orthogonal design of experiments was used to imitate the objective sound environments by reproducing the combinations of 8 sound characteristics, each with two levels. Then we defined 8 corresponding response variables to measure the subjective opinions towards the quality of reproduced sound. Finally, we applied the Multivariate Analysis of Valiance to explore the significant sound characteristics which affected the subjective opinions towards the quality of reproduced sound.

• Journal of the Korean School Mathematics Society
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• v.20 no.4
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• pp.369-385
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• 2017

This study is to figure out the activity and disposition of gifted students with face plot in exploratory data analysis at middle school mathematics class. This study has begun on the basis of the doing mathematics at multivariate analysis beyond one variable and two variables. Gifted students were developed the good learning habits theirselves. According to this result, Many gifted students have an interesting experience at data analysis with Face Plot. And they felt the useful methods of creative thinking about graphics with doing mathematics at mathematical tasks. I think that teachers need to learn the visualization methods and to make and to develop the STEAM education tasks connected real life. It should be effective enough to change their attitudes toward teaching and learning at exploratory data analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.421-421
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• 2017

In order to secure the safety of coastal areas from the continuous storm surge in Korea, it is important to predict the wave movement and properties accurately during the storm event. To improve the accuracy of the storm simulation, and to quantify coastal risks from the storm event, the dependencies between wave height, wave period, and storm duration should be analyzed. In this study, therefore, copulas were used to develop multivariate statistical models of sea storms. A case study of the east coast of Korea was conducted, and the dependencies between wave height, wave period, water level, storm duration and storm interarrival time were investigated using Kendall's tau correlation coefficient. As a result of the study, only wave height, wave period, and storm duration appeared to be correlated.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.55-63
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• 2019

In engineering problems, many random variables have correlation, and the correlation of input random variables has a great influence on reliability analysis results of the mechanical systems. However, correlated variables are often treated as independent variables or modeled by specific parametric joint distributions due to difficulty in modeling joint distributions. Especially, when there are insufficient correlated data, it becomes more difficult to correctly model the joint distribution. In this study, multivariate kernel density estimation with bounded data is proposed to estimate various types of joint distributions with highly nonlinearity. Since it combines given data with bounded data, which are generated from confidence intervals of uniform distribution parameters for given data, it is less sensitive to data quality and number of data. Thus, it yields conservative statistical modeling and reliability analysis results, and its performance is verified through statistical simulation and engineering examples.

• Water for future
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• v.24 no.4
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• pp.59-66
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• 1991

Abstract The purpose of the synthetic of monthly river flows based on the short-term observed data by means of multivariate stochastic models is to provide abundunt input data to the water resources systems of which the system performance and operation policy are to be determined beforehand. In this study, multivariate Thomas-Fiering and Matalas models for synthetic generation based on stream flows in neihboring basin were employed to check if it can be applide in the modeling of monthly flows. Statistical parameters estimated by Method of Moment and Fourier Series Analysis respectively were reproduced for statistical features. For comparisons the statistical parameters of the generated monthly flow by each model were compared with those of the observed monthly flows. Results of this study suggest that the application of Matalas model for synthetic generation of monthly river flows can be adapted.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.359-359
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• 2020

현재 우리나라의 가뭄감시 정보는 기상학적/농업적/수문학적 가뭄이 별도의 지수로 개발되어 다양한 형태의 정보를 생산·제공되고 있다. 각각의 가뭄 지수들 기준 및 특성에 따라 분석되고 있기 때문에 가뭄전문가의 입장에서는 매우 정밀한 가뭄정보를 제공받는 장점이 있는 반면에, 일반 국민들이 가뭄 정보를 받아들이고 이해하는데 어려움이 있어 이를 한눈에 알아볼 수 있는 통합가뭄지도가 필요하며, 통합가뭄도를 제작하기 위해서는 통합가뭄지수가 개발되어야 한다. 본 연구에서는 원격탐사자료를 활용하여 농업적 가뭄지수인 Agricultural Dry Condition Index (ADCI)와 수문학적 가뭄지수인 Water Budget-based Drought Index (WBDI)를 개발하였으며, 기상학적 가뭄지수인 Standardized Precipitation Index (SPI)를 포함하여 기상-농업-수문학적 가뭄지수를 결합한 통합가뭄지수를 산정하였다. 다양한 가뭄지수를 활용하여 개발되었기 때문에 다변량 통계 모형 중 선형 모형인 Principal Component Analysis (PCA)기법과 비선형 모형인 Kernel Entropy PCA, Kernel PCA를 적용하였다. 또한 과거 가뭄사상을 활용하여 산정된 통합가뭄지수 검증을 위해 과거 가뭄사상에 대한 가뭄 발생시기, 심도, 쇠퇴패턴이 양상 평가 및 Intentionally Biased Bootstrap Resampling (IBBR)을 활용한 지수별 민감도 분석을 통해 통합가뭄지수 적용성 평가를 진행하였다.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.903-913
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• 2013

Social network services generate a considerable amount of social data every day on personal feelings or thoughts. This social data provides changing patterns of information production and consumption but are also a tool that reflects social phenomenon. We analyze negative emotional words from daily blogs to detect the change in blooger sentiment using multivariate control charts. We used the all the blogs produced between 1 January 2008 and 31 December 2009. Hotelling's T-square control chart control chart is commonly used to monitor multivariate quality characteristics; however, it assumes that quality characteristics follow multivariate normal distribution. The performance of a multivariate control chart is affected by this assumption; consequently, we introduce the support vector data description and its extension (K-control chart) suggested by Sun and Tsung (2003) and they are applied to detect the chage in blogger sentiment.

• Journal of Plant Biotechnology
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• v.39 no.3
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• pp.121-126
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• 2012

To determine whether FT-IR spectroscopy combined with multivariate analysis for whole cell extracts can be used to discriminate major leguminous plant at metabolic level, seed extracts of six leguminous plants were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR spectral data from seed extracts were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). The PCA could not fully discriminate six leguminous plants, however PLS-DA could successfully discriminate six leguminous plants. The hierarchical dendrogram based on PLS-DA separated the six leguminous plants into four branches. The first branch was consisted of all three Vigna species including Vigna radiata var. radiate, Vigna angularis var. angularis and Vigna unguiculata subsp. Unguiculata. Whereas Pisum sativum var. sativum, Glycine max L and Phaseolus vulgaris var. vulgaris were clustered into a separate branch respectively. The overall results showed that metabolic discrimination system were in accordance with known phylogenic taxonomy. Thus we suggested that the hierarchical dendrogram based on PLS-DA of FT-IR spectral data from seed extracts represented the most probable chemotaxonomical relationship between six leguminous plants.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.415-427
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• 2001

공간통계학에서는 다변량 공간자료에 대한 예측방법으로서 코크리깅 기법을 이용한다. 본 논문에서는 코크리깅을 위한 첫 번째 단계인 교차베리오그램의 추정에 대한 감도분석 대신에 일반통계학적 측면에서 주성분점수를 이용한 감도분석방법을 제안한다. 변수가 2개인 경우, 교차베리오그램에 대한 감조분석의 결과와 제안된 주성분점수를 이용한 감도분석의 결과를 비교해 본다. 모의실험을 통하여 제안한 방법의 타당을 검증하고, 실제 자료를 이용한 사례분석의 결과로써 재확인해 본다.