• 제목/요약/키워드: Principal Component Factor

검색결과 368건 처리시간 0.025초

회귀분석에 의한 TOC 농도 추정 - 오수천 유역을 대상으로 - (Application of Regression Analysis Model to TOC Concentration Estimation - Osu Stream Watershed -)

  • 박진환;문명진;한성욱;이형진;정수정;황경섭;김갑순
    • 환경영향평가
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    • 제23권3호
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    • pp.187-196
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    • 2014
  • The objective of this study is to evaluate and analyze Osu stream watershed water environment system. The data were collected from January 2009 to December 2011 including water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and discharge. The data were used for principle component analysis and factor analysis. The results are as followes. The primary factors obtained from both the principal component analysis and the factor analysis were BOD, COD, TOC, SS and T-P. Once principal component analysis and factor analysis have been performed with the collected data and then the results will be applied to both simple regression model and multiple regression model. The regression model was developed into case 1 using concentrations of water quality parameters and case 2 using delivery loads. The value of the coefficient of determination on case 1 fell between 0.629 and 0.866; this was lower than case 2 value which fell between 0.946 and 0.998. Therefore, case 2 model would be a reliable choice.The coefficient of determination between the estimated figure using data which was developed to the regression model in 2012 and the actual measurement value was over 0.6, overall. It can be safely deduced that the correlation value between the two findings was high. The same model can be applied to get TOC concentrations in future.

Cluster Analysis with Air Pollutants and Meteorological Factors in Seoul

  • Kim, Jae-Hee;Lim, Ji-Won
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.773-787
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    • 2003
  • Principal component analysis, factor analysis and cluster analysis have been performed to analyze the relationship between air pollutants and meteorological variables measured in 1999 in Seoul. In principal analysis, the first principal has been shown the contrast effect between $O_3$ and the other pollutants, the second principal has been shown the contrast effect between CO, $SO_2$, $NO_2$ and $O_3$, PM10, TSP. In factor analysis, the first factor has been found as PM10, TSP, $NO_2$ concentrations which are related with suspended particulates. As a result of cluster analysis, three clusters respectively have represented different air pollution levels, seasonal characteristics of air pollutants and meteorological situations.

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THE ANALYSIS AND DIAGNOSIS OF SOWN PASTURE VEGETATION 2. GROUPING AND CHARACTERIZATION THE SOWN AND WEED SPECIES BY MEANS OF PRINCIPAL COMPONENT ANALYSIS

  • Kawanabe, S.
    • Asian-Australasian Journal of Animal Sciences
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    • 제4권3호
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    • pp.245-250
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    • 1991
  • Analysis of the characteristics and the grouping of the species of sown and weeds in artificial pastures was studied applying the principal component analysis method. Presency and coverage of six sown species and fifteen weed species which occurred in pastures of under-grazing and optimumgrazing were subject to analysis. From field survey, species were divided into three groups: the group A included five species such as Festuca arundinacea, Lolium perenne and Dactylis glomerata, etc., the group B included eleven species such as Polygonum longisetum, Agrostis alba and Rumex obtusifolius, etc., and the group C included five species such as Miscanthus sinensis, Rubus palmatus and Artemisia princeps, etc. The group A species corresponded to good pasture conditions and management. On the contrary, the group C species occurred in poor pasture conditions with inadequate management. The group B species corresponded to intermediate pasture conditions and management. Interrelated pair species co-existing and species non-co-existing were discovered. Factor loading as negative for the group A species. positive for the group C species and positive but lower than the group C species for the group B species. From these results it is concluded that the principal component analysis seems to one of the useful tools for the analysis of characteristics of species and the diagnosis of sown pasture vegetation, although further studies are required to get more general information about species characteristics.

계절변동의 함수적 예측 (Functional Forecasting of Seasonality)

  • 이긍희
    • 응용통계연구
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    • 제28권5호
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    • pp.885-893
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    • 2015
  • 통계청과 한국은행 등 통계작성기관에서 이용되고 있는 계절조정은 연간 경제통계 작성시 시계열을 예측한 후 계절조정방법을 적용하여 1년 후 계절변동을 예측하고 원통계 작성시 원통계에서 이를 제거하여 계절조정계열을 작성하고 있다. 이 경우 계절변동을 효과적으로 예측하는 것이 계절조정계열의 품질 향상을 위해 무엇보다 중요하다. 계절변동은 1년 단위로 비슷한 함수적 형태를 지니면서 변하므로 계절변동은 일종의 함수적 시계열이다. 함수적 시계열은 함수적 주성분분석을 바탕으로 한 함수적 시계열모형으로 예측할 수 있다. 본 연구에서는 함수적 시계열 모형을 이용하여 향후 1년간 계절변동을 예측하는 방안을 마련하고 X-11 방식 등 기존의 예측방법과 비교하여 유용성을 파악하였다.

독립변수의 차원감소에 의한 Polynomial Adaline의 성능개선 (Performance Improvement of Polynomial Adaline by Using Dimension Reduction of Independent Variables)

  • 조용현
    • 한국산업융합학회 논문집
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    • 제5권1호
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    • pp.33-38
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    • 2002
  • This paper proposes an efficient method for improving the performance of polynomial adaline using the dimension reduction of independent variables. The adaptive principal component analysis is applied for reducing the dimension by extracting efficiently the features of the given independent variables. It can be solved the problems due to high dimensional input data in the polynomial adaline that the principal component analysis converts input data into set of statistically independent features. The proposed polynomial adaline has been applied to classify the patterns. The simulation results shows that the proposed polynomial adaline has better performances of the classification for test patterns, in comparison with those using the conventional polynomial adaline. Also, it is affected less by the scope of the smoothing factor.

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류마티스 관절염 환자가 지각하는 불확실성 개념의 요인분석 (Factor Analysis of Uncertainty Experienced by Patients having Rheumatoid Arthritis)

  • 유경희;이은옥
    • 근관절건강학회지
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    • 제4권2호
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    • pp.238-248
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    • 1997
  • This study was conducted to identify the characteristics of uncertainty in patients having rheumatoid arthritis. Subjects of the study constituted 528 patients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. A self report questionnaire was used to measure the uncertainty. Reliability coefficients of this instrument was found Cronbach's ${\alpha}=.84$. In data analysis, SPSS PC 6.0 computer program was utilized for descriptive statistics and factor analysis. Three factors were appointed on the basis of literature review for the principal component factor analysis method and Varimax Orthogonal Rotation. The results of factor analysis were as follows ; 1) Three factors for uncertainty were identified through the principal component analysis and varimax rotation, and these contributed 37.4% of the valiance in the total score. Twenty six items among the whole items in the scale loaded above .39 on one of 3 factors. 2) The naming of each factor was as follows : Factor 1 was 'ambiguity' and has 12 items, factor 2 was 'lack of information' and has 8 items, factor 3 was 'unpredictability' and has 7 items. 3) Cronbach's alpha for internal consistency was .84 for the total items and .81, .80, .50 for each of three subscales in that order.

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무주지역 수질특성자료의 통계학적 분석에 의한 소유역 구분 (Watershed Classification Using Statistical Analysis of water Quality Data from Muju area)

  • 한원식;우남칠;이기철;이광식
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제7권3호
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    • pp.19-32
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    • 2002
  • 본 연구는 무주군 적상산 부근에 위치하는 소유역에서 지표수의 수질과 인접한 천층지하수 수질사이의 관계 및 지질매체와 오염원의 유입에 의한 계절적인 변동을 규명하기 위하여 수행되었다. 8월과 10월 두 차례의 조사결과 이곳 지표수와 지하수 수질은 Ca-$HCO_3$유형이 주를 이루고 있었으며 인근 광산부근에서는 중금속에 의한 오염이 나타나고 있었다. 10월 조사시에 인가가 밀집한 지역에서는 질산성 질소의 의한 오염 또한 높게 나타나는 특징을 보이고 있다. 이러한 자료를 토대로 군집분석(Cluster Analysis)과 주성분 분석(Principal Component Analysis)을 실시하였으며, 군집분석결과 지표수는 5개의 그룹으로 구분되었고 지하수는 3개의 그룹으로 구분되었다. 주성분분석 결과는 군집분석 시에 나타난 결과를 효과적으로 지지하고 있으며 (1)지질매체의 수리지화학적 반응, (2)오염물질의 유입 (3) 인근광산에 의한 중금속 오염이 복합적으로 반응하여 나타난 결과로 해석된다.

Quantity Surveyors' Perception of Cost Impact Factors in Hong Kong Civil Engineering Projects

  • Chiu, Wai Yee Betty;Lau, Hat Lan Ellen
    • Journal of Construction Engineering and Project Management
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    • 제5권3호
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    • pp.1-9
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    • 2015
  • Project cost is an important concern in any construction project. Although there has been a lot of studies on factors affecting the cost of construction projects, there seems no consensus as what cost factors have direct influence on the cost of civil engineering projects. This study therefore aims to bridge the current knowledge gap by examining quantity surveyors' perception of the factor structure among nineteen costing attributes identified based on literature review. Questionnaire was used to elicit responses from quantity surveyors working in the Hong Kong construction industry. Principal component analysis is conducted to extract the factor structure of the cost attributes and the attributes are grouped into three factor components, namely the contract management factor, the project management factor and the monetary value factor. Understanding these cost impact factors could be crucial in managing civil engineering projects, since it allows the project stakeholders and quantity surveyors to take precautionary steps to identify the cost management problems and areas for improvement and could even help to avoid cost deviations in engineering projects.

성인 인터넷 중독진단 개선을 위한 요인분석 (Factor Analysis for Improving Adults' Internet Addiction Diagnosis)

  • 김종완;김희재
    • 한국지능시스템학회논문지
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    • 제21권3호
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    • pp.317-322
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    • 2011
  • 한국정보화진흥원에서 개발한 한국형 성인 인터넷 중독 자가진단 척도인 K-척도는 4가지 요인의 20 문항으로 구성되어 있으며, 사용자의 설문응답값으로 인터넷 중독을 진단한다. 기존의 연구는 대부분 인터넷 중독의 원인을 찾으려는 시도였으며, 청소년 대상으로 수집된 표본을 가지고 그들의 인터넷 중독진단이 수행되었다. 본 연구의 목적은 통계 기법의 주성분분석과 데이터마이닝 기법인 의사결정트리를 이용하여 K-척도의 사용자군 분류를 판정하는 주요인을 발견하는 것이다. 실험 결과로부터 K-척도를 구성하는 4가지 요인 중 내성 및 몰입 요인이 성인 인터넷 중독진단에 가장 큰 영향을 주는 요인임을 알 수 있었다.

주성분분석 및 군집분석을 이용한 제주도 지하수위 변동 유형 분류 및 특성 비교 (Classification and Characteristic Comparison of Groundwater Level Variation in Jeju Island Using Principal Component Analysis and Cluster Analysis)

  • 임우리;함세영;이충모
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제27권6호
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    • pp.22-36
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    • 2022
  • Water resources in Jeju Island are dependent virtually entirely on groundwater. For groundwater resources, drought damage can cause environmental and economic losses because it progresses slowly and occurs for a long time in a large area. Therefore, this study quantitatively evaluated groundwater level fluctuations using principal component and cluster analyses for 42 monitoring wells in Jeju Island, and further identified the types of groundwater fluctuations caused by drought. As a result of principal component analysis for the monthly average groundwater level during 2005-2019 and the daily average groundwater level during the dry season, it was found that the first three principal components account for most of the variance 74.5-93.5% of the total data. In the cluster analysis using these three principal components, most of wells belong to Cluster 1, and seasonal characteristics have a significant impact on groundwater fluctuations. However, wells belonging to Cluster 2 with high factor loadings of components 2 and 3 affected by groundwater pumping, tide levels, and nearby surface water are mainly distributed on the west coast. Based on these results, it is expected that groundwater in the western area will be more vulnerable to saltwater intrusion and groundwater depletion caused by drought.