• Journal of Microbiology and Biotechnology
• /
• 제10권4호
• /
• pp.476-481
• /
• 2000

A linear correlation, by the stepwise multiple regression analysis, was found between the sensory test of Sigumjang aroma and the gas chromatographic data which were transformed with logarithm. GC data is the most objective method to evaluate Sigumjang aroma. A multiple correlation coefficient and a determination coefficient of more than 0.9 were obtained at the 9th and 13th steps, respectively. At step 31, the coefficient of determination level of 0.95 was attained. The accuracy of its estimation became higher as the number of the variables entered into the regression model increased. Over 90% of the Sigumjang aroma was explained by 13 compounds indentified on GC. The contributing proportion of the peak 26 was the highest followed by peaks 57 (9.27%), 29 (7.51%), 54 (6.01%), 8 (5.99%), 49 (4.97%), and 13 (4.11%).

• 한국식품과학회지
• /
• 제36권1호
• /
• pp.75-80
• /
• 2004

본 연구에서는 맛성분과 관능검사자료를 중회귀 분석하여 보리간장 맛을 평가하였다. 단순상관에서는 proline, alanine, methionine, lysine, histidine, lavulinic acid, ${\alpha}$-ketogutaric acid 및 citric acid와 관능검사 점수사이의 상관계수가 유의성이 높은 것으로 나타났으며, threonine, serine, cystein, phenylalanine, succinic acid, arabinose, xylose 및 sucrose 둥의 성분은 관능검사 점수에 거의 상관이 없는 것으로 나타났다. 하지만 단순상관분석으로는 보리간장 맛의 품질을 측정하는 것이 불가능하였다. 중회귀 분석을 실시한 결과 결정계수가 0.93 이상을 나타내어 맛성분 함량과 중회귀식을 이용하여 보리간장 맛의 93%를 추정하는 것이 가능하였다.

• 한국소음진동공학회논문집
• /
• 제20권2호
• /
• pp.172-178
• /
• 2010

The multiple regression analysis and path analysis in each dominant area of noise source are conducted to analyze the relationship between dependent variables like annoyance and independent ones such as noise and non-noise factors. The multiple regression analysis shows that impact of noise factors is the highest to annoyance in dominant areas of road traffic and railway noise. Meanwhile, impact of non-noise factors such as sensitivity and satisfaction of environment on annoyance is also high in these areas. The path analysis result for multivariate analysis between various independent and dependent variables is similar to that of the multiple regression analysis. However, noise factor is the greatest factor influent on annoyance in the dominant areas of the combined noise, and relationship between annoyance and sensitivity is the highest in combined area exposed to road traffic noise and railway noise.

• Ocean and Polar Research
• /
• 제34권2호
• /
• pp.185-195
• /
• 2012

This paper focused on forecasting a short-term production of oysters, which have been farmed in Korea, with distinct periodicity of production by year, and different production level by month. To forecast a short-term oyster production, this paper uses monthly data (260 observations) from January 1990 to August 2011, and also adopts several econometrics methods, such as Multiple Regression Analysis Model (MRAM), Seasonal Autoregressive Integrated Moving Average (SARIMA) Model, and Vector Error Correction Model (VECM). As a result, first, the amount of short-term oyster production forecasted by the multiple regression analysis model was 1,337 ton with prediction error of 246 ton. Secondly, the amount of oyster production of the SARIMA I and II models was forecasted as 12,423 ton and 12,442 ton with prediction error of 11,404 ton and 11,423 ton, respectively. Thirdly, the amount of oyster production based on the VECM was estimated as 10,425 ton with prediction errors of 9,406 ton. In conclusion, based on Theil inequality coefficient criterion, short-term prediction of oyster by the VECM exhibited a better fit than ones by the SARIMA I and II models and Multiple Regression Analysis Model.

• 산업경영시스템학회지
• /
• 제38권1호
• /
• pp.143-151
• /
• 2015

In this paper, we investigate how the power consumption of a heat pump dryer depends on various factors in the drying process by analyzing variables that affect the power consumption. Since there are in general many variables that affect the power consumption, for a feasible analysis, we utilize the principal component analysis to reduce the number of variables (or dimensionality) to two or three. We find that the first component is correlated positively to the entrance temperature of various devices such as compressor, expander, evaporator, and the second, negatively to condenser. We then model the power consumption as a multiple regression with two and/or three transformed variables of the selected principal components. We find that fitted value from the multiple regression explains 80~90% of the observed value of the power consumption. This results can be applied to a more elaborate control of the power consumption in the heat pump dryer.

• 디지털산업정보학회논문지
• /
• 제8권3호
• /
• pp.199-212
• /
• 2012

This study focuses on the influence of followership on leadership and empowerment, and to verify based on the control variables taken in IT SME's to enhance competitiveness through innovation and improvement plan that have been taken. Because there can be a lot of information to be taken, the laws of Moderated Regression Multiple analysis(MMR) were used. Amos, due to the moderating effect of Structural Equation Modeling(SEM) has been employed to re-verify the results seen with Moderated Regression Multiple analysis. The paper focuses on determining whether transformational leadership or transactional leadership is effective as shown by the levels of empowerment derived from these two types of leadership under study. As a result, both the Moderated Regression Multiple analysis and structural equation model searched information on transformational and followership for empowerment having moderating effects. In the Moderated Regression Multiple analysis, results showed that empowerment for leadership in business in the regulation of followership role appeared not to be seen. However, using the structural equation modeling, moderating effects have been found.

• 대한원격탐사학회지
• /
• 제35권4호
• /
• pp.503-516
• /
• 2019

We have estimated the vertical column density (VCD) of formaldehyde (HCHO) on a global scale using a multiple linear regression method (MRM) with Ozone Monitoring Instrument (OMI) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data. HCHO VCDs were estimated in regions of biogenic, pyrogenic, and anthropogenic emissions using independent variables, including $NO_2$ VCD, land surface temperature (LST), an enhanced vegetation index (EVI), and the mean fire radiative power (MFRP), which are strongly correlated with HCHO. To evaluate the HCHO estimates obtained using the MRM, we compared estimates of HCHO VCD data measured by OMI ($HCHO_{OMI}$) with those estimated by multiple linear regression equations (MRE) ($HCHO_{MRE}$). Good MRM performances were found, having the average statistical values (R = 0.91, slope = 1.03, mean bias = $-0.12{\times}10^{15}molecules\;cm^{-2}$, percent difference = 11.27%) between $HCHO_{MRE}$ and $HCHO_{OMI}$ in our study regions where high HCHO levels are present. Our results demonstrate that the MRM can be a useful tool for estimating atmospheric HCHO levels.

• 한국안전학회지
• /
• 제34권1호
• /
• pp.34-39
• /
• 2019

Flash point is the important indicator to determine fire and explosion hazards of liquid solutions. In this study, flash points of n-propanol+n-hexanol and n-butanol+n-hexanol systems were obtained by Seta flash tester. The methods based on UNIFAC equation and multiple regression analysis were used to calculate flash point. The calculated flash point was compared with the experimental flash point. Absolute average errors of flash points calculated by UNIFAC equation are $2.9^{\circ}C$ and $0.6^{\circ}C$ for n-propanol+n-hexanol and n-butanol+n-hexanol, respectively. Absolute average errors of flash points calculated by multiple regression analysis are $0.5^{\circ}C$ and $0.2^{\circ}C$ for n-propanol+ n-hexanol and n-butanol+n-hexanol, respectively. As can be seen from AAE, the values calculated by multiple regression analysis are noticed to be better than the values by the method based on UNIFAC eauation.

• 한국농공학회논문집
• /
• 제65권3호
• /
• pp.15-28
• /
• 2023

The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R² of 0.70 or more, and DNN analysis showed R² of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.

• Communications for Statistical Applications and Methods
• /
• 제14권2호
• /
• pp.281-286
• /
• 2007

Cook's distance is generalized to the multiple linear regression with linear constraints on regression coefficients. It is used for identifying influential observations in constrained regression models. A numerical example is provided for illustration.