• 한국경영과학회지
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• 제37권1호
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• pp.29-43
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• 2012

We design a DEA-AR model using multiple regression analysis with new methods which limit weights. When there are multiple input and single output variables, our model can be used, and the weights of input variables use the regression coefficient and coefficient of determination. To verify the effectiveness of the new model, we evaluate the efficiency of the Regional Corporations in Korea. Accordance with statistical analysis, it proved that there is no difference between the efficiency value of the DEA-AR using AHP and our DEA-AR model. Our model can be applied to a lot of research by substituting DEA-AR model relying on AHP in the future.

• 지역연구
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• 제14권2호
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• pp.35-50
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• 1998

This paper examines the determinants of imbalanced regional development in Korea during the period of 1985-1995. The review of previous analytical techniques have been used to analyze the determinants of disparities in regional development of disparities in regional development, but few has applied the regression technique which reduces a bias due to heterogeneity across region. The results of the study show that Kmenta model with per capita GRDP as dependent variable can reduce the heterogeneity bias in regional development and can minimize the statical errors in estimation and interpretation of the coefficients of the explanatory variables. According to the results of Kmenta model, urban infrastructure such as roads, information and communication facilities are major causes of regional disparity over the period of 1985-1995. The results of the study also indicate that local government should devote their policy efforts to identify and utilize the unique soci-economic characteristics of each locality in the process of regional development.

• 한국농공학회논문집
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• 제57권2호
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• pp.37-45
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• 2015

Typically, water quality sampling takes place intermittently since sample collection and following analysis requires substantial cost and efforts. Therefore regression models (or rating curves) are often used to interpolate water quality data. LOADEST has nine regression models to estimate water quality data, and one regression model needs to be selected automatically or manually. The nine regression models in LOADEST and auto-selection by LOADEST were evaluated in the study. Suspended solids data were collected from forty-nine stations from the Water Information System of the Ministry of Environment. Suspended solid data from each station was divided into two groups for calibration and validation. Nash-Stucliffe efficiency (NSE) and coefficient of determination ($R_2$) were used to evaluate estimated suspended solid loads. The regression models numbered 1 and 3 in LOADEST provided higher NSE and $R_2$, compared to the other regression models. The regression modes numbered 2, 5, 6, 8, and 9 in LOADEST provided low NSE. In addition, the regression model selected by LOADEST did not necessarily provide better suspended solid estimations than the other regression models did.

• 대한토목학회논문집
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• 제36권3호
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• pp.407-416
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• 2016

본 연구에서는 미계측 유역의 평균갈수량 추정을 위한 지역회귀모형을 개발하고자 하였다. 12개 다목적댐과 4개의 용수댐에서 관측된 조절되지 않은 유입량 자료로부터 평균갈수량을 산정하였고, 이를 유역면적, 유역경사, 유역밀도, 연평균강수량, 유출곡선지수 등의 유역특성인자와의 상관분석을 통해 다양한 형태의 지역회귀모형을 개발하였다. 평균갈수량의 관측값과 추정값의 비교를 통해 각 회귀모형의 성능을 평가하였고, 유역면적, 연평균강수량, 유출곡선지수를 설명변량으로 하는 회귀모형이 가장 우수한 성능을 보였다. 또한 비유량법과 기존에 개발된 기존회귀모형과의 비교를 통해서 본 연구에서 개발한 모형의 적용성이 가장 우수한 것으로 분석되었다.

• 보건행정학회지
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• 제26권4호
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• pp.271-278
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• 2016

Background: This study purposed to analyze the relationship between regional obesity rates and regional variables. Methods: Data was collected from the Korean Statistical Information Service (KOSIS) and Community Health Survey in 2012. The units of analysis were administrative districts such as city, county, and district. The dependent variable was the age-sex adjusted regional obesity rates. The independent variables were selected to represent four aspects of regions: health behaviour factor, psychological factor, socio-economic factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis model, this study applied geographically weighted regression (GWR) analysis to calculate the regression coefficients for each region. Results: The OLS results showed that there were significant differences in regional obesity rates in high-risk drinking, walking, depression, and financial independence. The GWR results showed that the size of regression coefficients in independent variables was differed by regions. Conclusion: Our results can help in providing useful information for health policy makers. Regional characteristics should be considered when allocating health resources and developing health-related programs.

• 한국수자원학회논문집
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• 제31권1호
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• pp.59-69
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• 1998

빈도별 홍수량의 지역분석을 위하여 유역의 지형특성을 독립변수로 이용하는 회귀모형을 검정하였다. 그런데 이들 독립변수들간의 상관관계가 존재할 경우 능형회귀모형이 이용되기도 하는 이 방법은 다중공선성 문제를 극복하는데 적합한 방법으로 알려져 있다. 능형회귀모형을 최적화하기 위해서는 조정변수가 포함되는 비용함수를 최소화하여야 한다. 본 연구에서는 이 최적화를 위하여 유전알고리즘을 이용하였다. 유전알고리즘은 자연 생물의 유전 및 진화과정을 모방한 추계학적 탐색방법을 말한다. 이러한 유전알고리즘을 이용하여 지역분석 모형을 검정한 결과 안정된 매개변수의 가중치를 얻을 수 있었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.

• 대한토목학회논문집
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• 제36권3호
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• pp.427-437
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• 2016

본 연구에서는 지형 및 기상학적 인자만으로 미계측 유역의 저유량부 유황곡선을 추정할 수 있는 지역회귀모형을 개발하고자 하였다. 이를 위해서 16개 유역의 계측 자료로부터 저유량 영역(지속일수 185일에서 365일)에 대한 유황곡선을 작성하고, 이를 토대로 로그형태의 이변수 회귀모형을 구축하였다. 이 회귀모형을 미계측 유역에 적용할 수 있도록 유역면적, 유역경사, 수계밀도, 연평균강수량, 연평균유출량, 유출곡선지수 등의 유역특성인자를 이용하여 모형의 매개변수를 지역화 하였다. 개발한 지역회귀모형으로 평균갈수량, 평균저수량, 평균평수량을 추정하여 관측값과 비교한 결과, 유역면적, 유출곡선지수, 연평균강수량 조합으로 구성된 지역회귀모형이 가장 우수한 것으로 분석되었다.

• 도시과학
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• 제9권1호
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• pp.41-49
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• 2020

This study analyzed the factors affecting economic growth using multiple regression model and Geographically Weighted Regression in consideration of population, industry and employment, housing and political characteristics on economic growth by region. The analysis results are summarized as follows. First, the total employment growth rate, manufacturing employment growth rate, local election turnout and the level of party consensus between the central and local governments are having a positive impact on regional economic growth. Second, according to the GWR analysis, the population has a positive impact on economic growth in the southern region of Korea, and the increase in the total number of employees has a positive impact on the southern region of Gyeonggi Province, Gangwon Province, North Chungcheong Province and North Gyeongsang Province. Finally, the voter turnout of urbanites is positively affecting economic growth in South Chungcheong Province, Gangwon Province and the southern coast, while North Jeolla and South Jeolla provinces have a positive impact on economic growth as the parties of the central and local governments are equal. The results of this study may suggest the role of local government for regional economic development.

• 한국산림과학회지
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• 제83권4호
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• pp.521-530
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• 1994

재적식(材積式)은 보통 흉고직경과 수고의 함수로 표현되는데, 회귀분석(回歸分析)을 통해 정확도가 높은 식이 주로 채택되고 있다. 우리나라에서도 지금까지 흉고직경(D)과 수고(H)를 독립변수로 하는 지수식(指數式)($V=aD^bH^c$)으로 각 수종에 대한 일반(一般)재적식을 유도하고 있다. 본 연구에서는 강원도 지방내의 홍천, 정선, 명주, 원주, 영월지역에 대한 간곡선식(幹曲線式)을 지역별로 유도하고, 이 간곡선식의 회전체(回轉體) 적분(積分)을 통해 지역별 재적을 직접 추정할 수 있는 간곡선 및 재적식 모델을 마련하였다. 조제된 모델에 의해 지역별로 추정된 재적은 기존의 강원도 지방 소나무재적표에 의해 추정된 재적에 비해 정확도가 높았다. 또한 지역간곡선식에 의해 유도된 간곡선의 형태는 지역에 따라 서로 달랐으며, 특히 영월지역과 원주지역의 수간은 다른 지역에 비해 수간상부에서 가늘게 발달하는 것으로 나타났다. 이와같은 간곡선의 다양한 형태는 재적추정에 있어서도 지역간 차이를 유발하였다.