• 제목/요약/키워드: Environmental Statistics

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추계강우모형에서의 강우통계의 시간적 변동성 연구 (Importance of the Temporal Variability of Rainfall Statistics in Stochastic Rainfall Modeling)

  • 김동균;이진우;조용식
    • 한국방재학회:학술대회논문집
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    • 한국방재학회 2010년도 정기 학술발표대회
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    • pp.51.2-51.2
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    • 2010
  • A novel approach of Poisson cluster stochastic rainfall generator was validated in its ability to reproduce important rainfall and watershed response characteristics at 104 locations of the United States. The suggested novel approach - The Hybrid Model(THM), as compared to the traditional ones, has an additional function to account for the year-to-year variability of rainfall statistics. The two-sample Kolmogorov-Smirnov test was used to see how well THM and traditional approach of Poisson cluster rainfall model reproduce the distribution of the following hydrologic variables: monthly maximum rainfall depths with 1, 3, 6, 12, and 24 hour duration, monthly maximum flow peaks at the virtual watersheds with Curve Number of 50, 60, 70, 80 and 90; and monthly runoff depths at the same virtual watersheds. In all of the testing variables, THM significantly outperformed the traditional approach. This result indicates that the year-to-year variability of rainfall statistics contains important information about the characteristics of rainfall processes that were not considered by the conventional approach of Poisson cluster rainfall modeling and that further considering it in rainfall simulation will enhance the performance of the rainfall models.

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수질관련 질환에 의한 한국인의 질병부담 (Burden of Disease Attributable to Water-related Diseases in Korea)

  • 황선빈;김형수;윤석준;이건세;김은정;조민우;오인환;김현진
    • 한국환경보건학회지
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    • 제37권4호
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    • pp.250-257
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    • 2011
  • Objectives: This study was aimed at re-assessing the environmental burden of disease attributable to waterrelated diseases using available local data from Korea. Methods: The general methods and the operational definitions for water, sanitation and hygiene applied to the study were based on an environmental burden of disease study conducted by WHO. Eleven water-related diseases were selected. The attributable fraction for diarrhea was calculated by assessing local exposure levels to drinking water, sanitation and hygiene according the scenario-based approach. The attributable fractions for the other ten diseases were derived from the results of the environmental burden of diseases study. The attributable DALYs were measured by using the attributable fractions and local health statistics. Results: The total environmental burden of disease attributable to water, sanitation and hygiene for Korea was 0.9210 DALY per 1000 capitals. Of the total burden of disease, the attributable burden of diarrhea was 0.8863 (96.1%), the attributable burden of malaria and malnutrition was 0.0236 and 0.0063 DALY per 1000 capitals, respectively. There was little burden of disease measured for other diseases. Conclusions: This study is meaningful in re-assessing the environmental burden of disease using available local exposure data and health statistics. Quantitative analysis of the environmental risk factors and a health impact assessment would be helpful to prioritize health policies or interventions in the future.

Discovery of Association Rules Using Latent Variables

  • Park, Hee-Chang;Cho, Kwang-Hyun
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2005년도 추계학술대회
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    • pp.177-188
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    • 2005
  • Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary threshold measures in association rule; support and confidence and lift. In the case of appling real world to association rules, we have some difficulties in data interpretation because we obtain many rules. In this paper, we develop the model of association rules using latent variables for environmental survey data.

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시간에 종속되는 스트렝스-스트레스 모형연구 - 스트렝스가 변하지 않는 경우 - (A Study on the Time Dependent Strength-Stress Model with Fixed Strength Case)

  • 이현우;김재주
    • 품질경영학회지
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    • 제24권3호
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    • pp.19-30
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    • 1996
  • We treat problems of estimating reliability R(t) = P[Y(t) > X(t)] in the time dependent strength-stress model in which a unit of stress X(t) is subjected to environmental strength Y(t) at time t. In this paper we introduce a special model of R(t) with fixed strength and unaccumulated stress case, and propose a Mann-Whitney-Wilcoxon type estimator of R(t).

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Discovery of Association Rules Using Latent Variables

  • Park, Hee-Chang;Cho, Kwang-Hyun
    • Journal of the Korean Data and Information Science Society
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    • 제17권1호
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    • pp.149-160
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    • 2006
  • Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary threshold measures in association rule; support and confidence and lift. In the case of appling real world to association rules, we have some difficulties in data interpretation because we obtain many rules. In this paper, we develop the model of association rules using latent variables for environmental survey data.

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Exploration of Association Rules for Social Survey Data

  • Park, Hee-Chang;Cho, Kwang-Hyun
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2005년도 춘계학술대회
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    • pp.18-24
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    • 2005
  • The methods of data mining are decision tree, association rules, clustering, neural network and so on. Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. We analyze Gyeongnam social indicator survey data by 2003 using association rule technique for environment information. Association rules are useful for determining correlations between attributes of a relation and have applications in marketing, financial and retail sectors. We can use association rule outputs in environmental preservation and environmental improvement.

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Industrial Waste Database Analysis Using Data Mining Techniques

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • 제17권2호
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    • pp.455-465
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    • 2006
  • Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, and relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. We analyze industrial waste database using data mining technique. We use k-means algorithm for clustering and C5.0 algorithm for decision tree and Apriori algorithm for association rule. We can use these outputs for environmental preservation and environmental improvement.

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Association Rule Mining by Environmental Data Fusion

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • 제18권2호
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    • pp.279-287
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    • 2007
  • Data fusion is the process of combining multiple data in order to produce information of tactical value to the user. Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. In this paper, we develop was macro program for statistical matching which is one of five branch types for data fusion. And then we apply data fusion and association rule techniques to environmental data.

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울산광역시 아황산가스(SO2)의 최적관측소 평가방법 (Method for Evaluating Optimal Air Monitoring Sites for SO2 in Ulsan)

  • 임정현;윤상후
    • 한국환경과학회지
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    • 제26권9호
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    • pp.1073-1080
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    • 2017
  • Manufacturing and technology industries produce large amounts of air pollutants. Ulsan Metropolitan City, South Korea, is well-known for its large industrial complexes; in particular, the concentration of $SO_2$ here is the highest in the country. We assessed $SO_2$ monitoring sites based on conditional and joint entropy, because this is a common method for determining an optimal air monitoring network. Monthly $SO_2$ concentrations from 12 air monitoring sites were collected, and the distribution of spatial locations was determined by kriging. Mean absolute error, Root Mean Squared Error (RMSE), bias and correlation coefficients were employed to evaluate the considered algorithms. An optimal air monitoring network for Ulsan was suggested based on the improvement of RMSE.

Translation method: a historical review and its application to simulation of non-Gaussian stationary processes

  • Choi, Hang;Kanda, Jun
    • Wind and Structures
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    • 제6권5호
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    • pp.357-386
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    • 2003
  • A number of methods based on various ideas have been proposed for simulating the non-Gaussian stationary process. However, these methods have some limitations. This paper reviewed several simulation methods based on the translation method using logarithmic and polynomial functions, which have emerged in the history of statistics and in the field of civil engineering. The applicability of each method is discussed from the viewpoint of the reproducibility of higher order statistics of the object function in the simulated sample functions, and examined using pressure signals measured from wind tunnel experiments for various shapes of buildings. The parameter estimation methods, i.e. the method of moments and quantile plot, are also reviewed, and the useful aspects of each method are discussed. Additionally, a simple worksheet for parameter estimation is derived based on the method of moment for practical application, and the accuracy is discussed comparing with a set of previously proposed formulae.