• The Journal of the Korea Contents Association
• /
• v.7 no.7
• /
• pp.133-143
• /
• 2007

The object of this study is to empirically analyze the effects of information support quality and service quality on service satisfaction of department store. To investigate the purpose of this study, literature review and survey were conducted. for statistical analysis, factor analysis, analysis of variance(ANOVA), and regression in order by the contingency grouping method were used. In conclusion of this study are as follows First, The regression analysis had effects on information support quality and service satisfaction. Second, The Analysis of variance(ANOVA) and regression had effects on information support quality and service satisfaction as service quality factors. Result, The information support accuracy and service quality had additional effect about customer relation.

• Advances in Computational Design
• /
• v.3 no.1
• /
• pp.87-112
• /
• 2018

In this study, it is aimed to present engineering software to estimate the structural response of concrete arch dam. Type-1 concrete arch dam constructed in the laboratory is selected as a reference model. Finite element analyses and experimental measurements are conducted to show the accuracy of initial model. Dynamic analyses are carried out by spectrum analysis under empty reservoir case considering soil-structure interaction and fixed foundation condition. The displacements, principal stresses and strains are presented as an analysis results at all nodal points on downstream and upstream faces of dam body. It is seen from the analyses that there is not any specific ratio between prototype and scaled models for each nodal point with different scale values. So, dynamic analyses results cannot be generalized with a single formula. To eliminate this complexity, the regression analysis, which is a statistical method to obtain the real model results according to the prototype model by using fitting curves, is used. The regression analysis results are validated by numerical solutions using ANSYS software and the error percentages are examined. It is seen that 10% error rates are not exceeded.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.4
• /
• pp.593-601
• /
• 2017

In this paper, we constructed the model of production/investment, distribution, and screening by using variables that can be considered at each stage according to the value chain stage of the movie industry. To increase the predictive power of the model, a regression analysis was used to derive meaningful variables. Based on the given variables, we compared the difference in predictive power between the artificial neural network, which is a machine learning analysis method, and the decision tree analysis method. As a result, the accuracy of artificial neural network was higher than that of decision trees when all variables were added in production/ investment model and distribution model. However, decision trees were more accurate when selected variables were applied according to regression analysis results. In the screening model, the accuracy of the artificial neural network was higher than the accuracy of the decision tree regardless of whether the regression analysis result was reflected or not. This paper has an implication which we tried to improve the performance of movie prediction model by using machine learning analysis. In addition, we tried to overcome a limitation of linear approach by reflecting the results of regression analysis to ANN and decision tree model.

• Spatial Information Research
• /
• v.22 no.3
• /
• pp.35-46
• /
• 2014

Population data are usually provided at administrative spatial units in Korea, so areal interpolation is needed for fine-grained analysis. This study aims to compare various methods of areal interpolation for population subgroups rather than the total population. We estimated the number of elderly people and single-person households for small areal units from Dong data by the different interpolation methods using 2010 census data of Seoul, and compared the estimates to actual values. As a result, the performance of areal interpolation methods varied between the total population and subgroup populations as well as between different population subgroups. It turned out that the method using GWR (geographically weighted regression) and building type data outperformed other methods for the total population and households. However, the OLS regression method using building type data performed better for the elderly population, and the OLS regression method based on land use data was the most effective for single-person households. Based on these results, spatial distribution of the single elderly was represented at small areal units, and we believe that this approach can contribute to effective implementation of urban policies.

• Geomechanics and Engineering
• /
• v.30 no.1
• /
• pp.11-26
• /
• 2022

One of the most important issues in tunneling, is the squeezing phenomenon. Squeezing can occur during excavation or after the construction of tunnels, which in both cases could lead to significant damages. Therefore, it is important to predict the squeezing and consider it in the early design stage of tunnel construction. Different empirical, semi-empirical and theoretical-analytical methods have been presented to determine the squeezing. Therefore, it is necessary to examine the ability of each of these methods and identify the best method among them. In this study, squeezing in a part of the Alborz service tunnel in Iran was estimated through a number of empirical, semi- empirical and theoretical-analytical methods. Among these methods, the most robust model was used to obtain a database including 300 data for training and 33 data for testing in order to develop a machine learning (ML) method. To this end, three ML models of Gaussian process regression (GPR), artificial neural network (ANN) and support vector regression (SVR) were trained and tested to propose a robust model to predict the squeezing phenomenon. A comparative analysis between the conventional and the ML methods utilized in this study showed that, the GPR model is the most robust model in the prediction of squeezing phenomenon. The sensitivity analysis of the input parameters using the mutual information test (MIT) method showed that, the most sensitive parameter on the squeezing phenomenon is the tangential strain (ε_θ^α) parameter with a sensitivity score of 2.18. Finally, the GPR model was recommended to predict the squeezing phenomenon in tunneling projects. This work's significance is that it can provide a good estimation of the squeezing phenomenon in tunneling projects, based on which geotechnical engineers can take the necessary actions to deal with it in the pre-construction designs.

• Water for future
• /
• v.28 no.4
• /
• pp.195-204
• /
• 1995

New dispersion coefficient equation which can be used to estimate dispersion coefficient by using only hydraulic data easily obtained in natural streams has been developed. Dimensional analysis was performed to select physically meaningful parameters, One-Step Huber method, which is one of the nonlinear multi-regression method, was applied to derive a regression equation of dispersion coefficient. 59 measured hydraulic data which were collected in 26 streams in the United States and were analyzed in the Part I of this study, were used in developing new dispersion coefficient equation. Among 59 measured data sets, 35 data sets were used in deriving regression equation, and 24 data sets are used for verification. The new dispersion coefficient equation, which has been developed in this study was proven to be superior in explaining dispersion characteristics of natural streams more precisely compared to existing dispersion coefficient equations.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.6 no.4
• /
• pp.43-52
• /
• 1986

With increasing of computer use, a least squares method is now widely used in the regression analysis of various data. Unreliable results of regression coefficients due to the floating point of computer and problems of ordinary least squares method are described in detail. To improve these problems, a least squares method using orthogonal function is developed. Also, Comparison and analysis are performed through an example of numerical test, and re-orthogonalization method is used to increase the accuracy. As an example of application, the optimum order of AR process for the time series of monthly flow at the Pyungchang station is determined using Akaike's FPE(Final Prediction Error) which decides optimum degree of AR process. The result shows the AR(2) process is optimum to the series at the station.

• Journal of the Korean Society for Precision Engineering
• /
• v.25 no.1
• /
• pp.99-107
• /
• 2008

There are being a lot of studies for achievement of high speed Dehydration, high-strength and Lightweight of washing machine in the latest washing machine business. It is essential that strength of mechanical press-Joining (MPJ) for spin drum is improved to attain that target. MPJ of spin drum is composed of seaming and caulking process. Because Seaming process of MPJ has various design factors such as thickness, bending radius, seaming width, caulking press width and the dynamic factor such as multistage plastic working, elastic recovery, residual stress, the optimum conditions can't be easily determined. Using a design of experiment (DOE) based on the FEM (Finite Element Method), which has several advantages such as less computing, high accuracy performance and usefulness, this study was performed investigating the interaction effect between the various design factor as well as the main effect of the each design factor during drum MPJ and proposed optimum condition using center composition method among response surface derived from regression equation of simulation-based DOE.

• KIEAE Journal
• /
• v.8 no.2
• /
• pp.41-46
• /
• 2008

Owing to a space covered by glass, atrium is an attractive space with a possibility as an inner public space but a typical building type with a high-energy load. From the aspect of global environmental issues, to reduce energy load is an important assignment to solve. Contriving a planning guideline of an opening is considered as the most effective environment adjustment method, to offer a highly assessed amenity space and secure openness to outside, keep the energy load to a minimum, and apply the natural energy such as daylight to a maximum at the same time. Users' assessment of environment was performed by questionnaire survey, then the structure of users' assessment was analyzed and design condition was regulated by multiple regression analysis. The opening design guideline to offer a highly assessed space was proposed with concrete environment adjustment method.

• Transactions of Materials Processing
• /
• v.11 no.5
• /
• pp.394-404
• /
• 2002

The drawbead model for a three-dimensional a finite element analysis of sheet metal forming processes is developed. The mathematical models of the basic drawbeads like circular drawbead, stepped drawbead, and squared drawbaed are first derived using the bending theory, belt-pulley equation, and Coulomb friction law. Next, the experiments for finding the drawing characteristics of the drawbead are performed. Based on mathematical models and drawing test results, expert models of basic drawbeads are then developed employing a linear multiple regression method. For the expert models of combined drawbeads such as the double circular drawbead, double stepped drawbead, circular-and-stepped drawbead, etc., those of the basic drawbeads are summed. Finally, in order to verify the expert models developed, the drawing characteristics calculated by the expert models of the double circular drawbead and circular-and-stepped drawbead are compared with those obtained from the experiments. The predictions by expert models agree well with the measurements by experiments.