• 한국물환경학회지
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• 제30권1호
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• pp.8-15
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• 2014

In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

• 산업기술연구
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• 제25권A호
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• pp.57-65
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• 2005

In this paper, for the highly plastic marine soft clay distributed in west and southern coast of Korean peninsula of Kwangyang and Busan New Port areas, correlation between compression index and other indices representing geotechnical engineering properties such as liquid limit, void ratio and natural water content were analyzed. Appropriate empirical equations of being able to estimate the compressibility of clays in the specific areas were proposed and compared with other existing empirical ones. For analyses of the data and test results, data for marine clays were used from areas of the South Container Port of the Busan New Port, East Breakwater, Passenger Quay, Jungma Reclamation and Reclamation Containment in the 3rd stage in Kwangyang. In order to find the best regression model by using the commercially available software, MS EXCEL 2000, results obtained from the simple linear regression analysis, using the values of liquid limit, initial void ratio and natural water content as independent variables, were compared with the existing empirical equations. Multiple linear regression was also performed to find the best fit regression curves for compression index and other soil properties by combining those independent variables. On the other hands, another software of SPSS for non-linear regression was used to analyze the correlations between compression index and other soil properties.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.37-46
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• 2023

The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

• 한국지리정보학회지
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• 제17권3호
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• pp.147-159
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• 2014

높은 수준의 TOD(대중교통 지향형 도시개발 : Transit Oriented Development)계획요소는 도시민의 대중교통 이용수요를 상승시키고 이는 지역의 보행환경을 개선하는 결과를 가져올 수 있다. 일반적으로 TOD 계획요소는 역세권 주변의 토지이용에 대한 다양성과 대중교통의 접근성, 그외 도시디자인 측면에서 평가되어 왔다. 특히 지하철역을 중심으로 하는 역세권 개발의 특성상 TOD 계획요소의 공간특성은 주변지역의 범위설정에 의존적일 가능성이 존재한다. 또한 물리적 TOD계획요소 이외에 지역의 사회경제적 특성 또한 대중교통의 수요에 큰 영향을 미칠 수 있다. 따라서 TOD에 관한 연구 시 권역설정에 따른 계획요소의 공간특성 변화와 해당지역의 사회경제적 특성을 주목할 필요가 있다. 본 연구에서는 부산시 지하철 역 주변을 대상으로 상이한 공간단위별로 도출된 TOD 계획 수준의 변화를 분석하였다. 또한 지하철 이용객 수와의 다중회귀분석을 통해 효과적인 TOD계획요소의 분석 공간단위를 탐색하였다. 이와 병행하여 사회경제적 요소를 추가적으로 적용한 다중 회귀모형과의 비교분석을 수행하여 TOD계획지표 이외에 사회경제적 변수의 적용 가능성을 검토하였다. 분석결과 공간단위의 설정에 따라 TOD계획지표의 공간분포에 변동성을 발견하였고 연구지역에서 효과적으로 적용 가능한 특정 공간단위를 도출하였다. 또한 물리적 TOD계획요소 이외에 추가적으로 사회경제적 변수를 적용한 다중 회귀모형이 보다 개선된 추론결과를 도출하였다.

• 대한교통학회지
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• 제10권3호
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• pp.103-122
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• 1992

The objective of this research is to develop a traffic accident forecasting model using traffic accident data in pusan from 1963 to 1991 and then to make short-term forecasts('93~'94) of traffic accidents in pusan. In this research, several forecasting models are developed. They include a multiple regression model, a time-series ARIMA model, a Logistic curve model, and a Gompertz curve model. Among them, the model which shows the most significance in forecasting accuracy is selected as the traffic accident forecasting model. The results of this research are as followings. 1. The existing model such as Smeed model which was developed for foreign countries shows only 47.8% explanation for traffic accident deaths in Korea. 2. A nonliner regression model ($R^2$=0.9432) and a Logistic curve model are appeared to be th gest forecasting models for the number of traffic accidents, and a Logistic curve model shows th most significance in predicting the accident deaths and injuries. 3. The forecasting figures of the traffic accidents in pusan are as followings: . In 1993, 31, 180 accidents are predicted to happen, and 430 persons are predicted to be deaths and 29, 680 persons are predicated to be injuries. . In 1994, 33, 710 accidents are predicted to happen, and 431.persons are predicted to be deat! and 30, 510 persons are predicted to be injuried. Therefore, preventive measures against traffic accidents are certainly required.

• 한국터널지하공간학회 논문집
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• 제26권1호
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• pp.39-58
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• 2024

TBM (Tunnel boring machine)은 터널 굴착 과정에서 여러 디스크 커터를 이용하여 암석을 절삭한다. 디스크 커터는 암석과의 지속적인 접촉과 마찰로 인해 마모된다. 디스크 커터의 표면이 마모되면 절삭 능력이 감소하고 굴착 효율이 떨어진다. 암석의 마모성은 디스크 커터 마모에 큰 영향을 미친다. 높은 마모도를 가진 암석은 커터에 더 큰 마모를 일으키며, 이는 디스크 커터의 수명을 단축시킨다. 세르샤 마모지수(Cerchar abrasivity index, CAI)는 암석의 마모성을 평가하는데 널리 사용되는 지표로 CAI는 암석의 마모특성을 나타내며, 디스크 커터의 수명과 성능 예측에 필수적인 요소로 인식되고 있다. 본 연구의 목적은 암석의 강도, 암석학적 특성과 선형회귀, 머신러닝 기법을 이용하여 CAI를 효과적으로 추정하는 새로운 방법을 개발하는 것이다. 문헌 조사를 통해 CAI, 일축압축강도, 압열인장강도, 등가석영함량이 포함된 데이터베이스를 구축하고 파생변수를 추가하였다. 통계적 유의성과 다중공선성을 고려하여 다중선형회귀분석을 위한 입력변수를 선정하였고, 머신러닝 모델의 입력변수는 변수중요도 분석을 통해 선정하였다. 머신러닝 예측모델 중 Gradient Boosting 모델의 예측 성능이 가장 높게 나타나 최적의 CAI 예측 모델로 선정되었다. 마지막으로 본 연구에서 도출한 다중선형회귀분석과 Gradient Boosting 모델의 예측 성능을 선행연구들의 CAI 예측모델과 비교하여 연구 결과의 타당성을 확인하였다.

• 농촌의학ㆍ지역보건
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• 제41권4호
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• pp.183-194
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• 2016

Objectives: The purpose of this study was to investigate the differences of capacity of local health organization to regional characteristics and the influence of organizational capacity on organizational performance. Methods: The study used the secondary data for 160 local public health organizations from $5^{th}$ Community Health Plans and 2009 Community Health Survey. The collected data were analyzed using one-way ANOVA and multiple regression analysis. Results: Work force and budget showed differences in regional size and elderly population rate. And consumer satisfaction and health care utilization showed differenced in work force and budget. The regression model with total number of employee, number of registered nurses, number of doctors and budget against consumer satisfaction was statistically significant (F=14.70, p=<.001), and number of registered nurses was identified as a factor influencing consumer satisfaction. This model also explained 20.5% of service satisfaction. The regression model for consumer satisfaction was statistically significant (F=45.98, p=<.001), and total number of employee nurses was identified as a factor influencing health care utilization. This model also explained 53.1% of utilization. Conclusions: The findings of this study imply that organizational capacity as work force and budget should be increased to improve the organizational performance as consumer satisfaction and health care utilization.

• 한국직업건강간호학회지
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• 제29권4호
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• pp.262-272
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• 2020

Purpose: This study aims to investigate the degree of job demand, job resources, burnout, and the organizational commitment of administrative nurses based on the job demands-resources model. Further, it seeks to confirm the influencing factors affecting nurses' burnout and organizational commitment. Methods: The participants were 188 administrative nurses working at hospitals (one tertiary hospital and six general hospitals) located in D City. The collected data were analyzed with IBM SPSS Statistics 23.0 using frequency, percentage, mean, standard deviation, t-tests, ANOVA, Pearson's correlation coefficient, and multiple regression analysis. Results: The influential factors of burnout were role conflict (β=.50), job demand (β=.18), job position (β=-.17, team leaders and above), and social support (β=-.15). The regression model had an explanatory power of 59%. The influential factors of organizational commitment were appropriate rewards (β=.59), job position (β=.15, team leader or above), working department (β=.14, referral center and health screening administration department), and social support (β=.18). The regression model had an explanatory power of 59.5%. Conclusion: The results support the job demands-resources model, and interventions should be developed to decrease job demand and provide sufficient job resources.

• 한국농공학회논문집
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• 제61권1호
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• pp.9-20
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• 2019

The primary objective of this study was to analyze the delivery ratio using Hydrological Simulation Program - Fortran (HSPF) in Okdong-cheon watershed. Model parameters related to hydrology and water quality were calibrated and validated by comparing model predictions with the 8-day interval filed data collected for ten years from the Korea Ministry of Environment. The results indicated that hydrology and water quality parameters appeared to be reasonably comparable to the field data. The pollutant delivery loads of the watershed in 2015 were simulated using the HSPF model. The delivery ratios of each subwatershed were also estimated by the simple ratio calculation of pollutant discharge load and pollutant delivery load. Coefficients of the regression equation between the delivery ratio and specific discharge were also computed using the delivery ratio. Based on the results, multiple regression analysis was performed using the discharge and the physical characteristics of the subwatershed such as the area. The equation of delivery ratio derived in this study is only for the Okdong-cheon watershed, so the larger studies are needed to apply the findings to other watersheds.

• Educational Technology International
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• 제15권2호
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• pp.71-88
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• 2014

A variety of studies to predict students' performance have been conducted since educational data such as web-log files traced from Learning Management System (LMS) are increasingly used to analyze students' learning behaviors. However, it is still challenging to predict students' learning achievement in blended learning environment where online and offline learning are combined. In higher education, diverse cases of blended learning can be formed from simple use of LMS for administrative purposes to full usages of functions in LMS for online distance learning class. As a result, a generalized model to predict students' academic success does not fulfill diverse cases of blended learning. This study compares two blended learning classes with each prediction model. The first blended class which involves online discussion-based learning revealed a linear regression model, which explained 70% of the variance in total score through six variables including total log-in time, log-in frequencies, log-in regularities, visits on boards, visits on repositories, and the number of postings. However, the second case, a lecture-based class providing regular basis online lecture notes in Moodle show weaker results from the same linear regression model mainly due to non-linearity of variables. To investigate the non-linear relations between online activities and total score, RF (Random Forest) was utilized. The results indicate that there are different set of important variables for the two distinctive types of blended learning cases. Results suggest that the prediction models and data-mining technique should be based on the considerations of diverse pedagogical characteristics of blended learning classes.