• Journal of Environmental Science International
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• v.16 no.11
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• pp.1301-1312
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• 2007

The objective of this study is to propose a critical storm duration forecasting model on storm runoff in small river basin. The critical storm duration data of 582 sub-basin which introduced disaster impact assessment report on the National Emergency Management Agency during the period from 2004 to 2007 were collected, analyzed and studied. The stepwise multiple regression method are used to establish critical storm duration forecasting models(Linear and exponential type). The results of multiple regression analysis discriminated the linear type more than exponential type. The results of multiple linear regression analysis between the critical storm duration and 5 basin characteristics parameters such as basin area, main stream length, average slope of main stream, shape factor and CN showed more than 0.75 of correlation in terms of the multi correlation coefficient.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.249-255
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• 2022

The COVID-19 virus appeared in 2019 and is extremely contagious. Because it is very infectious and has a huge impact on people's mobility. In this paper, multiple linear regression and random forest models are used to predict the number of COVID-19 cases using COVID-19 infection status data (open source data provided by the Ministry of health and welfare) and Google Mobility Data, which can check the liquidity of various categories. The data has been divided into two sets. The first dataset is COVID-19 infection status data and all six variables of Google Mobility Data. The second dataset is COVID-19 infection status data and only two variables of Google Mobility Data: (1) Retail stores and leisure facilities (2) Grocery stores and pharmacies. The models' performance has been compared using the mean absolute error indicator. We also a correlation analysis of the random forest model and the multiple linear regression model.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.3
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• pp.281-290
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• 2014

This study was conducted to evaluate the distribution characteristics of $PM_{10}$ and heavy metals concentrations in the ambient air of Gyeonggi-do area by region and season from February, 2013 to March, 2014. The regression model for the prediction of formation characteristics and contamination degree of $PM_{10}$ and heavy metals by correlation analysis and regression analysis for using the multivariate statistical analysis was also established. The main wind direction during the investigation period was South East (SE) and West South West (WSW) winds, and the concentration of $SO_2$ at Ansan with industrial region showed 1.6 times higher than Suwon, Euiwang with residential region. The concentrations (median) of Pb, Cu and Ni at Ansan showed 3.2~4.5, 1.9~2.2 and 1.7~2.6 times respectively higher than those at Suwon. By the seasonal concentration variation, the concentrations of $PM_{10}$, Pb, Fe and As in winter and spring (December to May) showed 1.7, 1.9, 1.9 and 2.7 times respectively higher than those in summer and fall (June to November). As, Fe and $PM_{10}$ had a big difference by the seasonal factors, and Cu and Ni were evaluated to be influenced by the regional factors. From the results of correlation analysis among the target items, the correlation coefficient of PM and Mn had 0.82 (p/0.01) and that of Fe and Mn had 0.82 (p/0.01), which showed high correlation. And the correlation coefficients for $SO_2$ and Pb, CO and $PM_{10}$ were 0.66 (p/0.01) and 0.62 (p/0.01) respectively. The multiple linear regression models for $PM_{10}$, Pb, Cu, Cr, As, Ni, Fe and Mn were established by independent variables of CO, $SO_2$ and meteorological factors (wind speed, relative humidity). In the regression models, independent variable $SO_2$ was in cause-and-effect relationship with all dependent variables, and $PM_{10}$, Fe and Mn were influenced by CO and wind speed, and Pb, Cu, Ni and As had a main factor of $SO_2$.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.105-112
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• 2015

The estimation of missing sensor values is an important problem in sensor network applications, but the existing approaches have some limitations, such as the limitations of application scope and estimation accuracy. Therefore, in this paper, we propose a new estimation model based on a spatial-temporal correlation analysis (STCAM). STCAM can make full use of spatial and temporal correlations and can recognize whether the sensor parameters have a spatial correlation or a temporal correlation, and whether the missing sensor data are continuous. According to the recognition results, STCAM can choose one of the most suitable algorithms from among linear interpolation algorithm of temporal correlation analysis (TCA-LI), multiple regression algorithm of temporal correlation analysis (TCA-MR), spatial correlation analysis (SCA), spatial-temporal correlation analysis (STCA) to estimate the missing sensor data. STCAM was evaluated over Intel lab dataset and a traffic dataset, and the simulation experiment results show that STCAM has good estimation accuracy.

• Journal of Environmental Science International
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• v.5 no.6
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• pp.763-770
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• 1996

This study was performed to analyze the variation characteristics of writer qulity, correlation analysis of water quality data at each site and among the items of water Quality data. Water quality for analysis was monthly values of water temperature, pH, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solid, 7-N and T-P checked in Daecheong Lake from January to December, 1995. It was analyzed variation of monthly water qulity was well from February to April, water temperature and COD seemed to have high correlationships at all sites. Regression equation is COD = 0.07 Water temperature +1.23 ($R^2$: 0.7616) . Results of the correlation analysis of water quality data showed that DO had high correlationships between site 1 and site 2, BOD did site 1 and 3, COD did site 1 and 2, 55 did site 5 and 6, 7-N did 2 and 3, 7-P did site 4 and 6. Regression equations for estimate of water quality data are as follows. $DO_1$=4.46+0.59 DO, ($R^2$=0.8868), $BOD_1$ = 0, 52+0.63 BOD3 ($R^2$ = 0.6390) $COD_2$ = 0.44+0.71 $COD_1$ ($R^2$ = 0.9183), SS6 = 0.89+0.7055.($R^2$ = 0.9155) $TN_3$ = 0.151 +0.886 $TN_2$ ($R^2$ = 0.9415), $TP_4$ = 0.004+5.758 $TP_6$ ($R^2$ = 0.9669)

• Journal of Fisheries and Marine Sciences Education
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• v.19 no.1
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• pp.19-28
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• 2007

The aim of this study is to analyze the frequency of the mark points of all examination subjects, the correlation between all examination subjects and the factors to influence pass of the examination. The methodology of this study are as follows.1. The descriptive analysis mark points of the examination subjects. 2. The correlation analysis between the examination subjects. 3. The multiple regression analysis among the examination subjects. Every mark points tend to be changed in wide ranges according to the student's learning ability. On the certificates examination for marine officers, Students in deck part recorded higher in rate of successful applicants, but showed more subject failure than those in engine part. It is especially suggested for the students to improve the teaching and learning skills of the subject. The high correlation subject to total and average points were found in English subject. The high correlation subject was shown between English & Ship handling, Engineering 1&2 and English & Engineering 1,2,3. The most influential subjects to pass the examination were Navigation, English, Engineering 3.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.9
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• pp.620-627
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• 2010

This paper presents a feasibility study of a fresh air load reduction system by using an underground double floor space. The fresh air is introduced into the double slab space and passes through the opening bored into the footing beam. The air is cooled by the heat exchange with the inside surface of the double slab space in summer, and heated in winter. This system not only reduces sensible heat load of the fresh air by heat exchange with earth but also reduces latent heat load of the fresh air by ad/de-sorption of underground double slab concrete. In this paper, we investigated the correlation between outdoor air temperature and outlet air temperature in the system. In conclusion, from the results of the high correlation we proposed a equation of regression for the outlet air temperature in the system by using linear regression analysis.

• Tribology and Lubricants
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• v.26 no.6
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• pp.329-335
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• 2010

Recently, the End-milling processing is needed the high-precise technique to get a good surface roughness and rapid time in manufacturing of precision machine parts and electronic parts. The optimum surface roughness has an effect on end-milling working condition such as, cutting direction, spindle speed, feed rate and depth of cut, and so on. It needs to form the correlation of working conditions and surface roughness. Therefore this study was carried out to presume of surface roughness on end-milling working condition of Al7075 by regression analysis. The results was shown that the coefficient of determination($R^2$) of regression equation had a fine reliability of 87.5% and nonlinear regression equation of surface rough was made by multiple regression analysis.

• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.29-37
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• 2015

Multi-household buildings are efficiently maintained from the mid- and long-term viewpoint according to the long-term repair coverage system etc. On the other hand, public buildings are not systematically maintained due to a lack of past maintenance cost data and inefficient budget plans, among other problems. Targeting public buildings in Incheon, this study analyzed operation costs variables. To verify the analysis results, they underwent a correlation analysis and a multi-regression analysis. With regard to public buildings electricity, gas and tap water cost, the influence power of the served life, floor area, and workforce were analyzed, revealing that electricity cost was highly correlated with workforce, while gas and tap water cost were correlated with tap water cost. Also, the correlation analysis results were verified through a multi-regression analysis, and a maintenance cost estimation model was presented using a regression equation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2010.05a
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• pp.225-228
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• 2010

It is an social issue that is various claim related on the defect of apartment house. The cost of defect repair is the most important matter that residents dispute constructers with the huge time wasting and cost loss. For resolve the matter of defect claim, it must to be analyze to the cost property that study and find to pending issue about the cost of defect repair. Therefore this study is investigated the cost property of defect repair relation on correlation analysis and regression analysis around the judgement cost. Consequently, cost of the judgment is associated with cost of the accusation and cost of the defect repair, is recognizable as them that is closely connected. Meanwhile, the more time of take effect and time of lawsuit increase, the more cost of the judgment decrease by draw the regression equation. On the contrary, there are same aspects in the case on the cost of the accusation and cost of the defect repair.