• 제목/요약/키워드: the multiple regression analysis

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다중회귀분석을 이용한 $CO_2$레이저 용접 비드 예측 (Estimation of $CO_2$ Laser Weld Bead by Using Multiple Regression)

  • 박현성;이세헌;엄기원
    • Journal of Welding and Joining
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    • 제17권3호
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    • pp.26-35
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    • 1999
  • On the laser weld production line, a slight alteration of the welding condition changes the bead size and the strength of the weldment. The measurement system is produced by using three photo-diodes for detection of the plasma and spatter signal in $CO_2$ laser welding. The relationship between the sensor signals of plasma or spatter and the bead shape, and the mechanism of the plasma and spatter were analyzed for the bead size estimation. The penetration depth and the bead width were estimated using the multiple regression analysis.

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수계 상류 관측 수위자료를 이용한 하류 홍수위 예측기법 (Forecasting Technique of Downstream Water Level using the Observed Water Level of Upper Stream)

  • 김상문;최병웅;이남주
    • Ecology and Resilient Infrastructure
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    • 제7권4호
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    • pp.345-352
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    • 2020
  • 최근 하천범람에 따른 피해를 최소화하기 위해서는 대피를 위한 선행시간을 확보하는 것이 매우 중요하다. 본 연구에서는 현재 하천에서 측정되고 있는 수위 관측 자료를 이용하여 이상호우 발생시 하류의 수위를 예측하였다. 수위 예측을 위해 다중회귀모형 및 인공신경망 모형을 섬강시험유역에 적용하였다. 다중회귀모형 및 인공신경망 모형의 학습에는 섬강시험유역의 2002년부터 2010년까지의 수위 관측 자료를 이용하였으며, 학습된 모형을 이용하여 발생 가능한 수위를 예측하였다. 모의 결과 인공신경망 수위예측모형의 결정계수는 0.991 - 0.999로 나타났으며, 다중회귀수위예측 모형의 결정계수는 0.945 - 0.990로 나타나 인공신경망을 이용한 수위예측모형이 다중회귀모형보다 좀 더 나은 예측 결과를 나타내는 것을 확인할 수 있었다. 본 연구결과는 향후 하천에서 선행시간을 확보한 홍수 예보 구축에 활용할 수 있을 것으로 판단된다.

다변량 분석법을 이용한 소양강댐 상류 유역의 하천 수질 평가 (Evaluation of Water Quality on the Upstreams of the Soyanggang Dam by using Multivariate Analysis)

  • 최한규;백효선;허준영
    • 산업기술연구
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    • 제22권A호
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    • pp.201-210
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    • 2002
  • The object of this study is to evaluate the factors affecting the water quality and to propose the influence of dominant factor quantitatively. The correlation analysis was performed to know the correlationship among the water quality items As a result of partial correlation analysis, it was shown that the water quality items are affected by the rainfall item directly. The factor analysis was performed to grasp some number of factors on each point for deducing the items of similar variable characteristics. The four points were divided into different factor groups. It was grasped that $NH_3-N$ and $NO_3-N$ Items have different variable characteristics after comparing the items. The Multiple regression analysis can decrease the number of observation. In the deduced multiple regression formula, it was shown that the rate of T-N, $NH_3-N$ and $NO_3-N$ in the independent variable took about 60% among all the regression formulas.

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Prediction of compressive strength of concrete using multiple regression model

  • Chore, H.S.;Shelke, N.L.
    • Structural Engineering and Mechanics
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    • 제45권6호
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    • pp.837-851
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    • 2013
  • In construction industry, strength is a primary criterion in selecting a concrete for a particular application. The concrete used for construction gains strength over a long period of time after pouring the concrete. The characteristic strength of concrete is defined as the compressive strength of a sample that has been aged for 28 days. Neither waiting for 28 days for such a test would serve the rapidity of construction, nor would neglecting it serve the quality control process on concrete in large construction sites. Therefore, rapid and reliable prediction of the strength of concrete would be of great significance. On this backdrop, the method is proposed to establish a predictive relationship between properties and proportions of ingredients of concrete, compaction factor, weight of concrete cubes and strength of concrete whereby the strength of concrete can be predicted at early age. Multiple regression analysis was carried out for predicting the compressive strength of concrete containing Portland Pozolana cement using statistical analysis for the concrete data obtained from the experimental work done in this study. The multiple linear regression models yielded fairly good correlation coefficient for the prediction of compressive strength for 7, 28 and 40 days curing. The results indicate that the proposed regression models are effectively capable of evaluating the compressive strength of the concrete containing Portaland Pozolana Cement. The derived formulas are very simple, straightforward and provide an effective analysis tool accessible to practicing engineers.

국적선사의 경쟁력 강화를 위한 한중정기항로 활성화 방안에 대한 실증연구 (An Empirical Study on the Activation Approach for the Competitive Power of Korean Shipping Company in the Korea-China Liner Routes)

  • 이용호
    • 한국항해항만학회지
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    • 제27권2호
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    • pp.163-170
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    • 2003
  • 본 연구는 한중정기항로에서 국적선사 활성화 방안에 관한 실증연구이다. 본 연구를 위하여 한중항로의 국적정기선사, 중국적 정기선사, 3국적 정기선사 등의 종사자에 실문지 500매를 배포하여 290매 회수하였으며, 한중정기항로 국적선사 활성화 요인과 물동량 증대효과의 관련성을 검증하기 위하여 먼저, 설문문항의 신뢰성(Reliability)은 크론바하 알파(Cronbach's Alpha)에 의한 내적 일관성 검사법을 통하여 검정하였고, 독립변수의 구성타당성(Construct Validity)을 검정하기 위해서 변수들이 선형결합이라는 가정 하에 요인을 추출하는 주성분 법(Principal Components)을 이용한 요인분석(Factor Analysis)을 실시하였다. 그리고 연구가설을 검증하기 위하여 다변량 회귀분석(Multiple Regression Analysis)을 실시하였다.

페이스북 활용 수업에서 대학생이 인식한 실재감이 학습몰입경험에 미치는 영향 (A Study on the Effects of Presence and Learning Flow Experience at University Classes Using Facebook)

  • 박혜진;유병민;차승봉
    • 농촌지도와개발
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    • 제22권3호
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    • pp.321-332
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    • 2015
  • For the purpose of enhancing the use of social service in classrooms, this research focuses on the relationships between presence and learning flow, key words in the analysis of college classes using Facebook. The results of this study are as follow. First, social presence(${\ss}=.33$, p=.000), emotional presence(${\ss}=.29$, p= .000), cognitive presence(${\ss}=.20$, p= .010) were found to be significant according to cognitive flow experience the result of analysis of multiple regression. all regression coefficients were positive. Second, emotional presence(${\ss}=.42$, p=.000) and social presence(${\ss}=.27$, p=.000), cognitive, presence(${\ss}=.17$, p=.015) were found to be significant according to emotional flow experience the result of analysis of multiple regression. all regression coefficients were positive. Third, social presence(${\ss}=.37$, p=.000) of the three variables were found to be significant according to behavioral flow experience the result of analysis of multiple regression.

Relationship between Aiming Patterns and Scores in Archery Shooting

  • Quan, ChengHao;Lee, Sangmin
    • 한국운동역학회지
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    • 제26권4호
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    • pp.353-360
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    • 2016
  • Objective: The aim of this study was to investigate the relationship between aiming patterns and scores in archery shooting. Method: Four (N = 4) elementary-level archers from middle school participated in this study. Aiming pattern was defined by averaged acceleration data measured from accelerometers attached on the body during the aiming phase in archery shooting. Stepwise multiple regression analysis was used to test whether a model incorporating aiming patterns from all nine accelerometers could predict the scores. In order to extract period of interest (POI) data from raw data, a Dynamic Time Warping (DTW)-based extraction method was presented. Results: Regression models for all four subjects are conducted with different significance levels and variables. The significance levels of the regression models are 0.12%, 1.61%, 0.55%, and 0.4% respectively; the $R^2$ of the regression models is 64.04%, 27.93%, 72.02%, and 45.62% respectively; and the maximum significance levels of parameters in the regression models are 1.26%, 4.58%, 5.1%, and 4.98% respectively. Conclusion: Our results indicated that the relationship between aiming patterns and scores was described by a regression model. Analysis of the significance levels, variables, and parameters of the regression model showed that our approach - regression analysis with DTW - is an effective way to raise scores in archery shooting.

Outlier Identification in Regression Analysis using Projection Pursuit

  • Kim, Hyojung;Park, Chongsun
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.633-641
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    • 2000
  • In this paper, we propose a method to identify multiple outliers in regression analysis with only assumption of smoothness on the regression function. Our method uses single-linkage clustering algorithm and Projection Pursuit Regression (PPR). It was compared with existing methods using several simulated and real examples and turned out to be very useful in regression problem with the regression function which is far from linear.

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Evaluation of Sigumjang Aroma by Stepwise Multiple Regression Analysis of Gas Chromatographic Profiles

  • Choi, Ung-Kyu;Kwon, O-Jun;Lee, Eun-Jeong;Son, Dong-Hwa;Cho, Young-Je;Im, Moo-Hyeog;Chung, Yung-Gun
    • Journal of Microbiology and Biotechnology
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    • 제10권4호
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    • pp.476-481
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    • 2000
  • A linear correlation, by the stepwise multiple regression analysis, was found between the sensory test of Sigumjang aroma and the gas chromatographic data which were transformed with logarithm. GC data is the most objective method to evaluate Sigumjang aroma. A multiple correlation coefficient and a determination coefficient of more than 0.9 were obtained at the 9th and 13th steps, respectively. At step 31, the coefficient of determination level of 0.95 was attained. The accuracy of its estimation became higher as the number of the variables entered into the regression model increased. Over 90% of the Sigumjang aroma was explained by 13 compounds indentified on GC. The contributing proportion of the peak 26 was the highest followed by peaks 57 (9.27%), 29 (7.51%), 54 (6.01%), 8 (5.99%), 49 (4.97%), and 13 (4.11%).

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패널자료의 무응답 대체법 (Non-Response Imputation for Panel Data)

  • 박기덕;신기일
    • Communications for Statistical Applications and Methods
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    • 제17권6호
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    • pp.899-907
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    • 2010
  • 무응답 대체(non-response imputation) 방법에 관한 많은 이론과 방법이 제안되었으며 실제 자료 분석에 이용되고 있다. 흔히 횡단면 무응답 대체를 위하여 다중대체법(multiple imputation)이 사용되고 있으며 2차년도 이상의 패널자료에는 종시점회귀대체법(cross-wave regression imputation)이 사용되고 있다. 본 연구에서는 패널자료 분석을 위하여 종시점회귀대체법의 일반형태인 시계열 대체법과 횡단면 무응답 대체법을 결합한 시계열-횡단면 다중 대체법을 제안하였다. 노동부의 매월노동통계 자료를 이용하여 제안한 방법과 기존의 종시점회귀대체법을 비교하여 우수함을 보였다.