• 제목/요약/키워드: Stepwise Multiple Regression model

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Models for Estimating Yield of Italian Ryegrass in South Areas of Korean Peninsula and Jeju Island

  • Peng, Jing Lun;Kim, Moon Ju;Kim, Byong Wan;Sung, Kyung Il
    • 한국초지조사료학회지
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    • 제36권3호
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    • pp.223-236
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    • 2016
  • The objective of this study was to construct Italian ryegrass (IRG) dry matter yield (DMY) estimation models in South Korea based on climatic data by locations. Obviously, the climatic environment of Jeju Island has great differences with Korean Peninsula. Meanwhile, many data points were from Jeju Island in the prepared data set. Statistically significant differences in both DMY values and climatic variables were observed between south areas of Korean Peninsula and Jeju Island. Therefore, the estimation models were constructed separately for south areas of Korean Peninsula and Jeju Island separately. For south areas of Korean Peninsula, a data set with a sample size of 933 during 26 years was used. Four optimal climatic variables were selected through a stepwise approach of multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the selected four climatic variables and cultivated locations as dummy variables was constructed. The model could explain 37.7% of the variations in DMY of IRG in south areas of Korean Peninsula. For Jeju Island, a data set containing 130 data points during 17 years were used in the modeling construction via the stepwise approach of multiple regression analysis. The model constructed in this research could explain 51.0% of the variations in DMY of IRG. For the two models, homoscedasticity and the assumption that the mean of the residuals were equal to zero were satisfied. Meanwhile, the fitness of both models was good based on most scatters of predicted DMY values fell within the 95% confidence interval.

방화 발생에 영향을 미치는 요인에 관한 연구 (A Study on the Factors Affecting the Arson)

  • 김영철;박우성;이수경
    • 한국화재소방학회논문지
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    • 제28권2호
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    • pp.69-75
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    • 2014
  • 본 연구에서는 방화발생에 영향을 미치는 요인을 도출하기 위하여 발생건수를 종속변수로 하고 경제 인구 사회적 요인을 독립변수로 하는 다중회귀분석을 실시하였다. 다중회귀분석은 선형함수, 준로그함수, 역준로그함수, 이중로그함수 4가지 함수형태에 대해 적용하였으며, 각 단계별로 변수의 선택과 제외를 고려하는 단계적선택 방식을 적용하였다. 다중공선성 문제와 자기상관 문제를 해결하기 위하여 분산확대지수(VIF)와 Durbin-Watson 계수 이용하였으며, 4가지 함수모형에 대하여 수정된 R 제곱(설명력) 값이 0.935 (93.5%)로 가장 값이 높고 통계적으로 유의한 선형함수모형을 최적의 모형으로 결정하고 모형에 대한 해석을 진행하였다. 선형함수모형 결과 방화발생에 영향을 미치는 요인은 범죄발생건수(0.829), 일반이혼율(0.151), 재정자주도(0.149), 소비자물가상승률(0.099) 순으로 도출되었다.

수박 내부결함판정을 위한 휴대형 압전형 장갑 센서시스템 (Portable Piezoelectric Film-based Glove Sensor System for Detecting Internal Defects of Watermelon)

  • 최동수;이영희;최승렬;김학진;박종민
    • Journal of Biosystems Engineering
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    • 제33권1호
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    • pp.30-37
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    • 2008
  • Dynamic excitation and response analysis is an acceptable method to determine some of physical properties of agricultural product for quality evaluation. There is a difference in the internal viscoelasticity between sound and defective fruits due to the difference of geometric structures, thereby showing different vibration characteristics. This study was carried out to develop a portable piezoelectric film-based glove sensor system that can separate internally damaged watermelons from sound ones using an acoustic impulse response technique. Two piezoelectric sensors based on polyvinylidene fluoride (PVDF) films to measure an impact force and vibration response were separately mounted on each glove. Various signal parameters including number of peaks, energy ratio, standard deviation of peak to peak distance, zero-crossing rate, and integral value of peaks were examined to develop a regression-estimated model. When using SMLR (Stepwise Multiple Linear Regression) analysis in SAS, three parameters, i.e., zeros value, number of peaks, and standard deviation of peaks were selected as usable factors with a coefficient of determination ($r^2$) of 0.92 and a standard error of calibration (SEC) of 0.15. In the validation tests using twenty watermelon samples (sound 9, defective 11), the developed model provided good capability showing a classification accuracy of 95%.

중회귀 모형을 이용한 울산지역 오존 포텐셜 모형의 설계 및 평가 (Design and Assessment of an Ozone Potential Forecasting Model using Multi-regression Equations in Ulsan Metropolitan Area)

  • 김유근;이소영;임윤규;송상근
    • 한국대기환경학회지
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    • 제23권1호
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    • pp.14-28
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    • 2007
  • This study presented the selection of ozone ($O_3$) potential factors and designed and assessed its potential prediction model using multiple-linear regression equations in Ulsan area during the springtime from April to June, $2000{\sim}2004$. $O_3$ potential factors were selected by analyzing the relationship between meterological parameters and surface $O_3$ concentrations. In addition, cluster analysis (e.g., average linkage and K-means clustering techniques) was performed to identify three major synoptic patterns (e.g., $P1{\sim}P3$) for an $O_3$ potential prediction model. P1 is characterized by a presence of a low-pressure system over northeastern Korea, the Ulsan was influenced by the northwesterly synoptic flow leading to a retarded sea breeze development. P2 is characterized by a weakening high-pressure system over Korea, and P3 is clearly associated with a migratory anticyclone. The stepwise linear regression was performed to develop models for prediction of the highest 1-h $O_3$ occurring in the Ulsan. The results of the models were rather satisfactory, and the high $O_3$ simulation accuracy for $P1{\sim}P3$ synoptic patterns was found to be 79, 85, and 95%, respectively ($2000{\sim}2004$). The $O_3$ potential prediction model for $P1{\sim}P3$ using the predicted meteorological data in 2005 showed good high $O_3$ prediction performance with 78, 75, and 70%, respectively. Therefore the regression models can be a useful tool for forecasting of local $O_3$ concentration.

Estimating excess post-exercise oxygen consumption using multiple linear regression in healthy Korean adults: a pilot study

  • Jung, Won-Sang;Park, Hun-Young;Kim, Sung-Woo;Kim, Jisu;Hwang, Hyejung;Lim, Kiwon
    • 운동영양학회지
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    • 제25권1호
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    • pp.35-41
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    • 2021
  • [Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R2) and 85.9% (adjusted R2), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R2) and 82.6% (adjusted R2), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R2) and 91.0% (adjusted R2), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

韓國河川의 月 流出量 推定을 위한 地域化 回歸模型 (Regionalized Regression Model for Monthly Streamflow in Korean Watersheds)

  • 김태철;박성우
    • 한국농공학회지
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    • 제26권2호
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    • pp.106-124
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    • 1984
  • Monthly streanflow of watersheds is one of the most important elements for the planning, design, and management of water resources development projects, e.g., determination of storage requirement of reservoirs and control of release-water in lowflow rivers. Modeling of longterm runoff is theoretically based on water-balance analysis for a certain time interval. The effect of the casual factors of rainfall, evaporation, and soil-moisture storage on streamflow might be explained by multiple regression analysis. Using the basic concepts of water-balance and regression analysis, it was possible to develop a generalized model called the Regionalized Regression Model for Monthly Streamflow in Korean Watersheds. Based on model verification, it is felt that the model can be reliably applied to any proposed station in Korean watersheds to estimate monthly streamflow for the planning, design, and management of water resources development projects, especially those involving irrigation. Modeling processes and properties are summarized as follows; 1. From a simplified equation of water-balance on a watershed a regression model for monthly streamflow using the variables of rainfall, pan evaporation, and previous-month streamflow was formulated. 2. The hydrologic response of a watershed was represented lumpedly, qualitatively, and deductively using the regression coefficients of the water-balance regression model. 3. Regionalization was carried out to classify 33 watersheds on the basis of similarity through cluster analysis and resulted in 4 regional groups. 4. Prediction equations for the regional coefficients were derived from the stepwise regression analysis of watershed characteristics. It was also possible to explain geographic influences on streamflow through those prediction equations. 5. A model requiring the simple input of the data for rainfall, pan evaporation, and geographic factors was developed to estimate monthly streamflow at ungaged stations. The results of evaluating the performance of the model generally satisfactory.

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기후 및 해양 요인과 김 생산량과의 관계에 관한 연구 (The Relationship between Climatic and Oceanographic Factors and Laver Aquaculture Production)

  • 김도훈
    • 수산경영론집
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    • 제44권3호
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    • pp.77-84
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    • 2013
  • While some steps in laver aquaculture production can be controlled artificially to a certain extent, the culturing process is largely affected by natural factors, such as the characteristics of seawater, climatic and oceanographic conditions, etc. This study aims to find a direct relationship between climatic and oceanographic factors (water temperature, air temperature, salinity, rainfall, sunshine duration and wind speed) and laver aquaculture production in Wando region, the biggest aquaculture production area of laver, located in the southwest coast of Korea using a multiple regression analysis. Despite the small sample size of a dependent variable, the goodness of model fit appeared acceptable. In addition, the R-squared value was 0.951, which means that the variables were very explanatory. Model results indicated that duration of sunshine, temperature, and rainfall during the farming period from the end of September to the end of April would be important factors affecting significantly to the laver aquaculture production.

다중 회귀 분석을 이용한 한자 난이도 예측 기법 연구 (Prediction Techniques for Difficulty Level of Hanja Using Multiple Linear Regression)

  • 최정환;노지우;김순태
    • 한국인터넷방송통신학회논문지
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    • 제19권6호
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    • pp.219-225
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    • 2019
  • 한자 급수와 같이 기존 한자 난이도 선정 방식에 문제점이 있다. 실생활에서 쓰이는 한글 단어와 차이가 나며 해당 급수가 실제로 얼마나 많이 쓰이는지 알 수가 없다. 이러한 문제를 해결하기 위해 빈도수를 이용하여 다중 회귀 분석을 이용하여 한자 난이도를 측정한다. 초등 교과서를 기반으로 한자활용빈도수와 한글의미빈도수를 집계한다. 두 빈도수와 획수를 함께 사용하여 설문지를 작성하여 해당 한자의 학습 적정 시기를 답변 받아 이를 회귀에서 사용할 타겟 변수로 이용한다. 단계별 회귀분석을 이용하여 적절한 피처를 선택하고 다중 선형 회귀 분석을 한다. 모델의 R2는 0.1105가 나왔으며 RMSE는 0.1105의 결과가 나왔다.

논토양의 이화학적 특성 및 침출성 중금속 함량을 이용한 비소의 전함량 예측 (Model Development for Estimating Total Arsenic Contents with Chemical Properties and Extractable Heavy Metal Contents in Paddy Soils)

  • 이정미;고우리;;류지혁;김지영;김두호;김원일
    • 한국토양비료학회지
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    • 제45권6호
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    • pp.920-924
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    • 2012
  • This study was performed to estimate total contents of arsenic (As) by stepwise multiple-regression analysis using chemical properties and extractable contents of metal in paddy soil adjacent to abandoned mines. The soil was collected from paddies near abandoned mines. Soil pH, electrical conductively (EC), organic mater (OM), available phosphorus ($P_2O_5$), and exchangeable cations (Ca, K, Mg, Na) were measured. Total contents of As and extractable contents of metals were analyzed by ICP-OES. From stepwise analysis, it was showed that the contents of extractable As, available phosphorus, extractable Cu, exchangeable K, exchangeable Na, and organic mater significantly influenced the total contents of As in soil (p<0.001). The multiple linear regression models have been established as Log (Total-As) = 0.741 + 0.716 Log (extractable-As) - 0.734 Log (avail-$P_2O_5$) + 0.334 Log (extractable-Cu) + 0.186 Log (exchangeable-K) - 0.593 Log (exchangeable-Na) + 0.558 Log (OM). The estimated value in total contents of As was significantly correlated with the measured value in soil ($R^2$=0.84196, p<0.0001). This predictive model for estimating total As contents in paddy soil will be properly applied to the numerous datasets which were surveyed with extractable heavy metal contents based on Soil Environmental Conservation Act before 2010.

Influencing Variables on Life Satisfaction of Korean Elders in Institutions

  • Sung, Ki-Wol
    • 대한간호학회지
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    • 제33권8호
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    • pp.1093-1110
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    • 2003
  • Purpose. The number of elders in institutions has increased as family supporting systems have changed in Korea. The purpose of this study were to understand the life satisfaction among elders in institutions and to identify the factors influencing on life satisfaction. Methods. The instruments used were Yun(1982)'s scale modified Memorial University of Newfoundland Scale for Happiness(MUNSH) in life satisfaction, ADL and IADL in activity level, Self-rating Depression Scale(SDS) in depression and Norbeck Social Support Questionnaire(NSSQ) scale in social support. Also, Perceived health status was measured by Visual Graphic Rating Scale. The subject of this study is 107 cognitively intact and ambulatory elders in 7 institutions in Daegu city and Kyungpook province. The data have been collected from May 1 to June 30, 2001. For the analysis of collected data, frequency analysis, mean, standard deviation, Pearson's correlation and stepwise multiple regression analysis were used for statistical analysis by SPSS win(version 9.0) program. Results. Life satisfaction for the elders in institutions showed negative correlation with SDS, and positive correlation with activity level. The regression form of the stepwise multiple regression analysis to investigate the influencing factors of life satisfaction for the elders in institutions was expressed by y =90.988-0. 733x1-0.188x2-0.069x3-0.565x4 (xl: SDS x2: Social support x3: Activity level x4: Monthly pocket Money) and 57.9% of varience in life satisfaction was explained by the model. Conclusion. The factors influencing on life satisfaction among the elders in institutions were SDS, social support, activity level and monthly pocket money. According to the results of this study, depression, social support and activity level are considered the prime causal factors for life satisfaction.