• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.10
• /
• pp.20-25
• /
• 2004

Using the multiple regression analysis cutting forces of turning processes have been predicted based on the cutting conditions such as feed rate(f), depth of cut(d), and cutting velocity(v). The statistical inference of the equation was checked by ANOVA test. The validity of the proposed regression analysis was verified by two sets of cutting tests of 27 cutting conditions and the additional cutting tests of 18 cutting conditions. From the results of analytical and experimental studies, it was found that there was no significant difference between the measured and predicted cutting forces. Also, the shear and friction characteristics of turning processes were analyzed with predicted cutting forces.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.21 no.5
• /
• pp.83-93
• /
• 2017

This study proposed the new weighting values and fault points of condition assessment items for reinforced earth retaining walls based on the combination the inspection data and hybrid weighting technique. Utilizing the inspection data of 161 reinforced earth retaining walls, multi regression analysis and entropy technique were applied to gain the weighting values of condition assessment items. In addition, the weighting values by AHP technique was analyzed based on the opinion of experts. By appling hybrid weighting technique to the calculated weighting values obtained by the individual technique, the new weighting values of condition assessment items were proposed, and the fault points and fault indices of reinforced earth retaining walls were proposed. Results showed that the rank of the weighting value of the condition evaluation items was fluctuated according to the multiple regression analysis, AHP technique, and entropy technique. There was no duplication of the rank of the weighting value while the current weighting value was overlapped. Specially, in the rsults of multi regression analysis, two condition assessment items were occupied 70% of the total weights. When the proposed weighting values were applied to existing reinforced earth retaining wall of 161, 16 reinforced earth retaining walls showed the increased risk rank and 31 represented the decreased risk rank.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2010.04a
• /
• pp.624-627
• /
• 2010

최근 자동차 업계서는 차량의 온실가스 배출량을 줄이고 연비를 개선시킬 수 있는 방법 중의 하나로 경량화 소재를 사용하여 차체의 중량을 줄이는 연구가 활발히 진행 중에 있다. 특히 알루미늄 합금의 경우 기존 강재에 비해 비중이 낮아 가볍고 부식에 대한 저항성이 높아 많이 사용되어지고 있는 추세이다. 본 연구에서는 먼저, 저입열 용접공정을 적용하여 용접 변수와 토치의 각도에 따른 인장강도 특성을 비교하여 적정 용접 범위를 산정하였으며, 인장강도와 비드형상의 관계를 다중 회귀 분석을 이용하여 비드 예측 회귀 모델을 제시하였다. 또한 호감도 함수를 적용한 반응표면분석법을 이용하여 자동차 생산 현장에서 겹치기 용접 이음부의 강건한 용접 품질을 가질 수 있는 최적용접 공정 조건을 도출할 수 있는 효과적인 방법을 제안하고자 한다.

• Economic and Environmental Geology
• /
• v.39 no.3 s.178
• /
• pp.255-268
• /
• 2006

Recent 22-year (1981-2002) meteorological data of 58 Korea Meteorological Adminstration (KMA) station were analyzed to investigate spatial and temporal variation of surface air temperature (SAT) and ground surface temperature (GST) in Korea. Based on the KMA data, multiple linear regression (MLR) models, having two regression variables of latitude and altitude, were presented to predict mean surface air temperature (MSAT) and mean ground surface temperature (MGST). Both models showed a high accuracy of prediction with $R^2$ values of 0.92 and 0.94, respectively. The prediction of MGST is particularly important in the areas of geothermal energy utilization, since it is a critical parameter of input for designing the ground source heat pump system. Thus, due to a good performance of the MGST regression model, it is expected that the model can be a useful tool for preliminary evaluation of MGST in the area of interest with no reliable data. By a simple linear regression, temporal variation of SAT was analyzed to examine long-term increase of SAT due to the global warming and the urbanization effect. All of the KMA stations except one showed an increasing trend of SAT with a range between 0.005 and $0.088^{\circ}C/yr$ and a mean of $0.043^{\circ}C/yr$. In terms of meteorological factors controlling variation of GST, the effects of solar radiation, terrestrial radiation, precipitation, and snow cover were also discussed based on quantitative and qualitative analysis of the meteorological data.

• Journal of Korean Society of Transportation
• /
• v.27 no.3
• /
• pp.149-160
• /
• 2009

The purpose of this study is to comparatively analyse the behavior patterns of the first and the repeated offenders in DWI, and to develope the models of BAC(Blood Alcohol Concentration) by using multiple regression analysis method and a model of repeated DWI conviction by using logistic regression analysis method. The main results are as follows. First, the repeated offenders are more in criminal and traffic accidents records than that of the first offenders. The unlicenced drivers are in higher BAC than licenced drivers. Second, multiple regression model of BAC was developed, and the model revealed that criminal records and driving distance were important factors. Third, a model of repeated DWI conviction was developed, and the model revealed that traffic accidents records, whether or not having licence, and criminal records were most important factors.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.4
• /
• pp.1693-1705
• /
• 2013

To restore old aqueduct in Korea which is a irrigation bridge to supply water in paddy field area, it is needed to estimate approximate costs of restoration because the basic design for estimation of construction costs is often ruled out in current system. In this paper, estimating models of construction costs were developed on the basis of performance data for restoration of RC aqueduct bridges since 2003. The regression analysis (RA) model and case-based reasoning (CBR) model for the estimation of construction costs were developed respectively. Error rate of simple RA model was lower than that of multiple RA model. CBR model using genetic algorithm (GA) has been applied in the estimation of construction costs. In the model three factors like attribute weight, attribute deviation and rank of case similarity were optimized. Especially, error rate of estimated construction costs decreased since limit ranges of the attribute weights were applied. The results showed that error rates between RA model and CBR models were inconsiderable statistically. It is expected that the proposed estimating method of approximate costs of aqueduct restoration will be utilized to support quick decision making in phased rehabilitation project.

• Korean Journal of Soil Science and Fertilizer
• /
• v.31 no.4
• /
• pp.359-367
• /
• 1998

In order to determine the nitrogen supplying capabilities (NSC) of corn fields, 47 field experiments were performed in Pennsylvania over 3 year from 1986 and NSCs were estimated by the regression analysis with chemical properties and soil attributes. Although the content of $NO_3-N$ in soil showed the best correlation with NSC ($R^2=0.518$), the standardized partial regression coefficient of $NO_3-N$ for NSC was 0.52, with some variations over the years. This value was slightly higher than those of the other properties which ranged from 0.001 to 0.351. Multiple linear regression with soil attributes for the evaluation of NSC was better than simple regression with $NO_3-N$. The coefficient of determination ($R^2$) for the evaluation of NSC was gradually increased; 0.599 with selected chemical properties, 0.698 with quantitative attributes(chemical properties and depth of Ap horizon), and 0.839 with quantitative and selected qualitative soil attributes. Consequently, in order to evaluate NSC, analysis by multiple linear regression with soil attributes was more reliable and better model than by the simple regression model.

• Korean Journal of Remote Sensing
• /
• v.33 no.2
• /
• pp.135-147
• /
• 2017

We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.

• Journal of Digital Convergence
• /
• v.16 no.11
• /
• pp.167-175
• /
• 2018

By conducting multiple regression analysis, we analyzed the major independent factors affecting user convenience and emotional factors, and identified the important functional elements in the design of the VR device, so that the functional elements to be developed can be grasped in advance. As a result of the study, satisfaction of handling of VR bicycle and satisfaction of speed control by paddling were considered as the most important technical factors as independent factors which have the greatest influence on user convenience and emotional factor among technical satisfaction. Also, it is possible to increase the probabilities of successful design by setting a model that predicts user convenience and the emotional part from the technical factors.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.4
• /
• pp.218-236
• /
• 2023

This study attempted to analyze the environmental equity of fine dust(PM₁₀) in Daegu using MGWR(Multi-scale Geographically Weighted Regression) and KT(Korea Telecom Corporation) sensor data. Existing national monitoring network data for measuring fine dust are collected at a small number of ground-based stations that are sparsely distributed in a large area. To complement these drawbacks, KT sensor data with a large number of IoT(Internet of Things) stations densely distributed were used in this study. The MGWR model was used to deal with spatial heterogeneity and multi-scale contextual effects in the spatial relationships between fine dust concentration and socioeconomic variables. Results indicate that there existed an environmental inequity by land value and foreigner ratio in the spatial distribution of fine dust in Daegu metropolitan city. Also, the MGWR model showed better the explanatory power than Ordinary Least Square(OLS) and Geographically Weighted Regression(GWR) models in explaining the spatial relationships between the concentration of fine dust and socioeconomic variables. This study demonstrated the potential of KT sensor data as a supplement to the existing national monitoring network data for measuring fine dust.