• 제목/요약/키워드: Simple Regression Analysis

검색결과 914건 처리시간 0.026초

회귀분석에 의한 건물에너지 사용량 예측기법에 관한 연구 (A Study for Predicting Building Energy Use with Regression Analysis)

  • 이승복
    • 설비공학논문집
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    • 제12권12호
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    • pp.1090-1097
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    • 2000
  • Predicting building energy use can be useful to evaluate its energy performance. This study proposed empirical approach for predicting building energy use with regression analysis. For the empirical analysis, simple regression models were developed based on the historical energy consumption data as a function of daily outside temperature, the predicting equations were derived for different operational modes and day types, then the equations were applied for predicting energy use in a building. BY selecting a real building as a case study, the feasibilities of the empirical approach for predicting building energy use were examined. The results showed that empirical approach with regression analysis was fairly reliable by demonstrating prediction accuracy of $pm10%$ compared with the actual energy consumption data. It was also verified that the prediction by regression models could be simple and fairly accurate. Thus, it is anticipated that the empirical approach will be useful and reliable tool for many purposes: retrofit savings analysis by estimating energy usage in an existing building or the diagnosis of the building operational problems with real time analysis.

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Statistical notes for clinical researchers: simple linear regression 3 - residual analysis

  • Kim, Hae-Young
    • Restorative Dentistry and Endodontics
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    • 제44권1호
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    • pp.11.1-11.8
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    • 2019
  • In the previous sections, simple linear regression (SLR) 1 and 2, we developed a SLR model and evaluated its predictability. To obtain the best fitted line the intercept and slope were calculated by using the least square method. Predictability of the model was assessed by the proportion of the explained variability among the total variation of the response variable. In this session, we will discuss four basic assumptions of regression models for justification of the estimated regression model and residual analysis to check them.

하천수내 TOC 농도 추정을 위한 단순회귀모형과 다중회귀모형의 개발과 평가 (Development and Evaluation of Simple Regression Model and Multiple Regression Model for TOC Contentation Estimation in Stream Flow)

  • 정재운;조소현;최진희;김갑순;정수정;임병진
    • 한국물환경학회지
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    • 제29권5호
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    • pp.625-629
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    • 2013
  • The objective of this study is to develop and evaluate simple and multiple regression models for Total Organic Carbon (TOC) concentration estimation in stream flow. For development (using water quality data in 2012) and evaluation (using water quality data in 2011) of regression models, we used water quality data from downstream of Yeongsan river basin during 2011 and 2012, and correlation analysis between TOC and water quality parameters was conducted. The concentrations of TOC were positively correlated with Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), TN (Total Nitrogen), Water Temperature (WT) and Electric Conductivity (EC). From these results, simple and multiple regression models for TOC estimation were developed as follows : $TOC=0.5809{\times}BOD+3.1557$, $TOC=0.4365{\times}COD+1.3731$. As a result of the application evaluation of the developed regression models, the multiple regression model was found to estimate TOC better than simple regression models.

The audit method of cooling energy performance in office building using the Simple Linear Regression Analysis Model

  • Park, Jin-Young;Kim, Seo-Hoon;Jang, Cheol-Young;Kim, Jong-Hun;Lee, Seung-Bok
    • KIEAE Journal
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    • 제15권5호
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    • pp.13-20
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    • 2015
  • Purpose: In order to upgrade the energy performance of existing building, energy audit stage should be implemented first because it is useful method to find where the problems occur and know how much time and cost consumption for retrofit. In overseas researches, three levels of audit is proposed whereas there are no standards for audit in Korea. Besides, most studies use dynamic simulation in detail like audit level 3 even though the level 2 can save time and cost than level 3. Thus, this paper focused on audit level 2 and proposed the audit method with the simple linear regression analysis model. Method: Two parameters were considered for the simple regression analysis, which were the monthly electric use and the mean outdoor temperature data. The former is a dependent variable and the latter is a independent variable, and the building's energy performance profile was estimated from the regression analysis method. In this analysis, we found the abnormal point in cooling season and the more detailed analysis were conducted about the three heat source equipments. Result: Comparing with real and predicted models, the total consumption of predicted model was higher than real value as 23,608 kWh but it was the results that was reflected the compulsory control in 2013. Consequently, it was analyzed that the revised model could save the cooling energy as well as reduce peak electric use than before.

연속강우시 산성우의 이온농도 변화에 관한 조사연구 (A Study on Ion Concentration Change of Acid Rain by the Succeeding Raintall)

  • 박경렬;김대선
    • 한국환경보건학회지
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    • 제16권2호
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    • pp.11-20
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    • 1990
  • To investigate ionic characteristics of acid rain by the succeeding rainfall. bulk precipitation was collected every each 5mm rainfall from march to october 1990 at Dae Jeon area. pH, sulfate nitrate, chloride, ammonium ion was measured and analyzed. The result was as follows: 1. The weighted average pH of rain was 5.1$\pm$ 0.72(4.15~7.6) and rain pH less than 5.5 was appeared 51.3% 2. Average ion concentrations of sulfate, nitrate, chloride and ammonium ion was 125.12 $\mu$eq/l, 62.38 $\mu$eq/l, 31.95 $\mu$eq/l, 66.6 $\mu$eq/l and rates of each anions was 57%, 28.4%, 14.6% and rate of sulfate by nitrate was 2 times. 3. There is no correlations time interval of rainfall and Ion concentration change. 4. From initial to 15mm rainfall, each ion concentrations were decreased. and average concentration of pH, SO$^{-2}_{4}$, Cl ion concentration was increased in the succeeding rainfall 5. Only sulfate ion was correlated by the simple regression analysis with pH except NO$^{-}_{3}$, Cl$^{-}$ and NH$_{4}^{+}$ Cl$^{-}$ correlation coefficient was very high at the multiple regression analysis with pH. 6. Simple & multiple correlation coefficient among anions and NH$^{+}_{4}$ was very high especially N$^{+}_{4}$ and SO$^{2-}_{4}$ at simple regression analysis and SO$^{-2}_{4}$ and NO$_{3}^{-}$, Cl$^{-}$, NH$_{4}^{-}$ at multiple regression analysis.

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A simple nonlinear model for estimating obturator foramen area in young bovines

  • Pares-Casanova, Pere M.
    • 대한수의학회지
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    • 제53권2호
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    • pp.73-76
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    • 2013
  • The aim of this study was to produce a simple and inexpensive technique for estimating the obturator foramen area (OFA) from young calves based on the hypothesis that OFA can be extrapolated from simple linear measurements. Three linear measurements - dorsoventral height, craneocaudal width and total perimeter of obturator foramen - were obtained from 55 bovine hemicoxae. Different algorithms for determining OFA were then produced with a regression analysis (curve fitting) and statistical analysis software. The most simple equation was OFA ($mm^2$) = [3,150.538 + ($36.111^*CW$)] - [147,856.033/DH] (where CW = craneocaudal width and DH = dorsoventral height, both in mm), representing a good nonlinear model with a standard deviation of error for the estimate of 232.44 and a coefficient of multiple determination of 0.846. This formula may be helpful as a repeatable and easily performed estimation of the obturator foramen area in young bovines. The area of the obturator foramen magnum can thus be estimated using this regression formula.

라소를 이용한 간편한 주성분분석 (Simple principal component analysis using Lasso)

  • 박철용
    • Journal of the Korean Data and Information Science Society
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    • 제24권3호
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    • pp.533-541
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    • 2013
  • 이 연구에서는 라소를 이용한 간편한 주성분분석을 제안한다. 이 방법은 다음의 두 단계로 구성되어 있다. 먼저 주성분분석에 의해 주성분을 구한다. 다음으로 각 주성분을 반응변수로 하고 원자료를 설명변수로 하는 라소 회귀모형에 의한 회귀계수 추정량을 구한다. 이 회귀계수 추정량에 기반한 새로운 주성분을 사용한다. 이 방법은 라소 회귀분석의 성질에 의해 회귀계수 추정량이 보다 쉽게 0이 될 수 있기 때문에 해석이 쉬운 장점이 있다. 왜냐하면 주성분을 반응변수로 하고 원자료를 설명변수로 하는 회귀모형의 회귀계수가 고유벡터가 되기 때문이다. 라소 회귀모형을 위한 R 패키지를 이용하여 모의생성된 자료와 실제 자료에 이 방법을 적용하여 유용성을 보였다.

단층핵 구성물질의 함량과 전단강도 사이의 상관성 분석 (Relationship between Shear Strength and Component Content of Fault Cores)

  • 윤현석;문성우;서용석
    • 자원환경지질
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    • 제52권1호
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    • pp.65-79
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    • 2019
  • 본 연구에서는 안산암질암, 화강암 및 퇴적암에서의 단층핵 시료에 대한 직접전단시험과 입도시험 결과를 이용하여 단순회귀분석과 다중회귀분석을 실시하고, 각력 및 점토 함량과 전단강도 사이의 상관성을 분석하였다. 수직응력(${\sigma}_n=54$, 108, 162 kPa) 및 암종별로 단순회귀분석을 수행한 결과, 전단강도는 각력의 함량과 비례 관계를 보이며, 점토의 함량과 반비례 관계를 보인다. 또한, 대부분의 암종에서 전단강도는 각력보다 점토와 높은 상관성을 보이며, 수직응력이 증가할수록 각력과 점토 함량의 변화에 큰 영향을 받는 것으로 분석되었다. 각력과 점토의 함량을 동시에 고려한 다중회귀분석에서 전단강도는 점토보다 각력 함량의 변화에 더 민감하게 반응하는 것으로 나타났다. 결과적으로, 단순회귀분석과 다중회귀분석으로부터 산정된 회귀모형들의 결정계수($R^2$)를 비교 분석함으로써 암종별로 가장 적합한 회귀 모형을 제안하였고, 제안된 모형들은 0.624~0.830의 높은 결정계수를 보인다.

미계측 유역의 부유물질 산정을 위한 다중회귀식 개발 (Development of Multiple Regression Equation for Estimation of Suspended Solids in Unmeasurable Watershed)

  • 최한규;박재용;박수진
    • 산업기술연구
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    • 제26권A호
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    • pp.119-127
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    • 2006
  • The purpose of this study is to present quantitatively the influence of variables that had the largest effect on the changes in suspended solids(SS), which would cause turbid water phenomenon, among water quality factors of the non-point pollution source, and then to develop a multiple regression equation of SS and predict the water quality of ungaged watersheds so as to provide basic data to establish efficient management plans for SS which flow in rivers and lakes. To identify the correlation of SS with the amount of rainfall and the state of land use, a simple correlation analysis and a simple regression analysis were conducted respectively. Finally, a multiple regression analysis was conducted to provide that SS were set as dependent variables while the amount of rainfall, paddy fields and dry fields were set as independent variables. As a result, the amount of rainfall had the most significant influence on changes in SS, followed by dry fields and paddy fields. In addition, the multiple regression equation was developed to predict SS in unmeasurable watersheds.

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