• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.465-480
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• 2009

In this study, single and multiple linear regression model were used to derive the relationship between precipitation and altitude, latitude and longitude in Jejudo. The single linear regression analysis was focused on whether orographic effect was existed in Jejudo by annual average precipitation, and the multiple linear regression analysis on whether orographic effect was applied to each duration and return period of quantile from regional frequency analysis by index flood method. As results of the regression analysis, it shows the relationship between altitude and precipitation strongly form a linear relationship as the length of duration and return period increase. The multiple linear regression precipitation estimates(which used altitude, latitude, and longitude information) were found to be more reasonable than estimates obtained using altitude only or altitude-latitude and altitude-longitude. Especially, as results of spatial distribution analysis by kriging method using GIS, it also provides realistic estimates for precipitation that the precipitation was occurred the southeast region as real climate of Jejudo. However, the accuracy of regression model was decrease which derived a short duration of precipitation or estimated high region precipitation even had long duration. Consequently the other factor caused orographic effect would be needed to estimate precipitation to improve accuracy.

• Journal of Environmental Science International
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• v.7 no.6
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• pp.827-831
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• 1998

Statistical $SO_2$ forecasting technique by multiple regression analysis was designed and developed to predict $SO_2$ concentration in Wonju City. $SO_2$ concentration data measured from air pollution monitoring system and meteorological factors data such as : wind speed, atmospheric stability, surface temperature, relative humidity and precipitation were used in Wonju City during the 1996~1997. As the results, correlation model for forecasting was well fitted with some parameters including minimum temperature, wind speed and the $SO_2$ concentration of the previous day.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.268-276
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• 2008

In highway construction projects, concrete pavement productivity has been challenged with constructors and decision-makers; at present there are few methods available to accurately evaluate the factors impacting on it. Any inefficient method to analyze it leads to the excessive schedule, higher rehabilitation costs, shorter service life, and reduction of ride quality. To implement these negative outcomes, constructors or decision-makers need a systematic tool that can be used to categorize the factors related to construction productivity. This paper applies multiple regression technique for productivity analysis of the Jointed Plane Concrete Pavement (JPCP), identifies the significant factors, and provides a predictive model assisting in monitoring and managing the productivity of the JPCP construction process. The completed and progressive projects are employed to derive and assess the proposed model. The results are analyzed to illustrate its capabilities.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.493-500
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• 2000

Rock Mass Rating has been widely applied to the underground tunnel excavation and many other practical problems in rock engineering. However, Rock Mass Rating is hard to make out because it is difficult to estimate each valuation items through all kind of field situations and items of RMR have interdependence. So the experts of tunnel assessment have problems with rating rock mass. In this study, using multivariate analysis based on domestic data(1011EA) of water conveyance tunnel, we presented rock mass rating system which is objective and easy to use. The constituents of RMR are decided to RQD, condition of discontinuities, groundwater conditions, orientation of discontinuities, intact rock strength, spacing of discontinuities in important order. In each step, we proposed the best multiple regression model for RMR system. And using data which have been collected at other site, we examined that presented multiple regression model was useful.

• Journal of the Korean Home Economics Association
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• v.30 no.3
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• pp.193-204
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• 1992

The purpose of this article is (1) to measure the attitudes of health care consumers towards medical service, the physicians' duty to provide information and patient self-determination options, (2) to discover the their related variables. The attitude of health care consumers towards medical service reveals statistically significant corelation with age and education. Among the statistically significant independent variables it is significantly related with age in the multiple regression analysis. The attitude of health care consumers towards the physicians' duty to provide information reveals statistically significant corelation with age, education and the attitude of health care consumers towards medical service. Among these independent variables it is significantly related with the attitude of health care consumers towards medical service in the multiple regression analysis. The attitude of health care consumers towards patients' self-determination options reveals statistically significant corelation with age, the attitude of health care consumers towards medical service and the attitude of health care consumers towards the physicians' duty to provide information. Among these independent variables it is significantly related with the attitude of health care consumers towards the physicians' duty to provide information in the multiple regression analysis.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.111-112
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• 2013

Architecture has a large influence in the environment and human health. Therefore eco-friendly concept and sustainable development are important in Architectural field. This study aims to analyze impact of green building rating system on an apartment housing CO₂ emission using multiple regression analysis. But in this result, green building rating system has no effect on CO₂ emission. So, future study is required to analyze factors of green building rating system on the CO₂ emission.

• Journal of Korean Society of Rural Planning
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• v.2 no.2
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• pp.103-108
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• 1996

In rural planning, the cost estimation of project is a key factor for planning. Therefore, development of reliable cost estimation method is essential. Recently, new techniques are suggested for determination of project cost using historical cost data. In this study, a multiple-regression analysis was used to determine the cost of the farm land consolidation. The results demonstrated that multiple regression analysis using historical cost data can be applicable to project cost estimation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.3
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• pp.98-105
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• 2019

In the past 30 years, our aviation demand has been growing continuously. As such, the importance of the demand forecasting field is increasing. In this study, the factors influencing Korea's international air demand were selected, and the international air demand was analyzed, forecasted and reviewed through OLS multiple regression analysis. As a result, passenger demand was affected by GDP per capita, oil price and exchange rate, while cargo demand was affected by GDP per capita and private consumption growth rate. In particular, passenger demand was analyzed to be sensitive to temporary external shocks, and cargo demand was more affected by economic variables than temporary external shocks. Demand forecasting, OLS multiple regression analysis, passenger demand, cargo demand, transient external shocks, economic variables.

• Journal of Environmental Health Sciences
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• v.35 no.3
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• pp.191-200
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• 2009

We investigated a trait of odor and the relationship between odor unit and odorous compounds using multiple regression analysis based on data compiled from Sihwa (SIC), Banwol (BIC), Banwol plating (BPIC) and Poseung industrial complex (PIC). These areas are odor control areas in Gyeonggi province. It was revealed that $NH_3$ and styrene concentrations in SIC and BPIC were relatively higher and $H_2S$ concentration especially in mc was more than five times higher than other areas. As a result of regression analysis using SAS, intensity of odor unit was highly related to concentrations of $H_2S$, TMA, styrene and n-valeraldehyde in SIC, $H_2S$, acetaldehyde, and butyraldehyde in BPIC and $NH_3$ in BIC.

• Geomechanics and Engineering
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• v.29 no.3
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• pp.219-228
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• 2022

The most widely used parameter to represent rock abrasiveness is the Cerchar abrasivity index (CAI). The CAI value can be applied to predict wear in TBM cutters. It has been extensively demonstrated that the CAI is affected significantly by cementation degree, strength, and amount of abrasive minerals, i.e., the quartz content or equivalent quartz content in rocks. The relationship between the properties of rocks and the CAI is investigated in this study. A database comprising 223 observations that includes rock types, uniaxial compressive strengths, Brazilian tensile strengths, equivalent quartz contents, quartz contents, brittleness indices, and CAIs is constructed. A linear model is developed by selecting independent variables while considering multicollinearity after performing multiple regression analyses. Machine learning-based regression methods including support vector regression, regression tree regression, k-nearest neighbors regression, random forest regression, and artificial neural network regression are used in addition to multiple linear regression. The results of the random forest regression model show that it yields the best prediction performance.