• Advances in Computational Design
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• v.7 no.2
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• pp.113-128
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• 2022

Water consumption is strongly affected by numerous factors, such as population, climatic, geographic, and socio-economic factors. Therefore, the implementation of a reliable predictive model of water consumption pattern is challenging task. This study investigates the performance of predictive models based on multi-layer perceptron (MLP), multiple linear regression (MLR), and support vector regression (SVR). To understand the significant factors affecting water consumption, the stepwise regression (SW) procedure is used in MLR to obtain suitable variables. Then, this study also implements three predictive models based on these significant variables (e.g., SWMLR, SWMLP, and SWSVR). Annual data of water consumption in Thailand during 2006 - 2015 were compiled and categorized by provinces and distributors. By comparing the predictive performance of models with all variables, the results demonstrate that the MLP models outperformed the MLR and SVR models. As compared to the models with selected variables, the predictive capability of SWMLP was superior to SWMLR and SWSVR. Therefore, the SWMLP still provided satisfactory results with the minimum number of explanatory variables which in turn reduced the computation time and other resources required while performing the predictive task. It can be concluded that the MLP exhibited the best result and can be utilized as a reliable water demand predictive model for both of all variables and selected variables cases. These findings support important implications and serve as a feasible water consumption predictive model and can be used for water resources management to produce sufficient tap water to meet the demand in each province of Thailand.

• Journal of the Korean Home Economics Association
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• v.33 no.4
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• pp.173-188
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• 1995

This study examined the characteristics of the relationship of HOME, sociodemographic variables and children's verbal ability at age four, five, six, Expecially this study investigated causal relationships amoong the variables which are supposed to affect children's verbal ability by children's age and sex. The subject of this study were 180 children and their mothers. Instruments included inventory of home stimulation(HOME), inventory of socio-demographic variables, inventory of the children's verbla ability. The results obtained from this study were as follows : 1. For the most part, HOME and socio-demographic variables had a significant positive correlation with children's verbal ability. 2. The variables that significantly predicted children's verbal ability differed according to children's age and sex. That is, play materials, breadth of experience and economic status of the home were predictive of boy's verbal ability at age four, while aspects of physical environment, breadth of experience were predictive at age five, fostering maturity and independence, parent's education were predictive at age six. And developmental stimulation and breadth of experience were predictive of girl's verbal ability at age four, while developmental stimulation, economic status of the home were predictive at age five, developmental stimulation and play materials were predictive at age six. 3. the results of the analysis of the causal model showed that the kind of variables that affected children's verbal ability directly differed according to children's age and sex. That is, indirect stimulation and direct stimulation affected boy's verbal ability directly at age four and five, while indirect stimulation and parent's education affected boy's verbal ability at age six. And indirect stimulation, direct stimulation, emotional climate of the home affected girl's verbal ability directly at age four, while direct stimulation, economic status of the home, indirect stimulation affected directly at age five, parent's education, indirect stimulation and direct stimulation affected girl's verbal ability at age six. 4. Another causal model of the HOME, socio-demographic variables affecting children's verbal ability showed that total HOME scores more significantly affected boys and girl's verbal ability directly than socio-demographic variables at all ages.

• Human Ecology Research
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• v.52 no.3
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• pp.275-284
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• 2014

This study was designed to examine the relationships between empowerment and child care teachers' intention of teaching, the reason for teaching intent. The subjects were 181 child care teachers from Chungcheongnamdo and the city of Daejeon, Korea. This study was conducted using questionnaires. The results were as follows: first, there were significant relationships between empowerment and child care teachers' intention of teaching and, the reason for teaching intent. There were positive relationships between decision making, professional growth, status, self-efficacy, autonomy, impact empowerment and child care teacher' intention of teaching and, the reason for teaching intent. Second, child care teachers' intention of teaching and the reason for teaching intent were affected by empowerment. Status and professional growth empowerment were the most predictive variables for the child care teachers' intention of teaching. The impact and self-efficacy empowerment were the most predictive variables for enjoy working with children, impact and professional growth empowerment were the most predictive variables for finding meaning in teaching, impact and status empowerment were the most predictive variables for opportunities to face ongoing challenges, and achievement motive. Status empowerment were the most predictive variable for reasonable pay and working environment, stability and skill. Therefore, status and impact empowerment were the most predictive variable for the reason for teaching intent.

• The Research Journal of the Costume Culture
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• v.1 no.2
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• pp.113-130
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• 1993

The purpose of this study was to investigate the role of perceived attributes of innovation in predicting the fashion innovativeness of female college students and to compare results with the predictive efficacy of selected psychographic variables. The data were analyzed by factor analysis and stepwise multiple regression. Frequency, percentage and man values were used to evaluate the descriptive data. The major findings derived from analysis are as follows: 1. Of the psychographic variables used to predict fashion innovativeness fashion interest was the most predictive of fashion innovativeness followed by venturesomeness. 2. So only perceived attributes variables found to be predictive of fashion innovativeness was perceived risk.

• KIEAE Journal
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• v.15 no.4
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• pp.105-110
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• 2015

Purpose: This study aimed at finding the optimal input variables of the artificial neural network-based predictive model for the optimal controls of the indoor temperature environment. By applying the optimal input variables to the predictive model, the required time for restoring the current indoor temperature during the setback period to the normal setpoint temperature can be more precisely calculated for the cooling season. The precise prediction results will support the advanced operation of the cooling system to condition the indoor temperature comfortably in a more energy-efficient manner. Method: Two major steps employing the numerical computer simulation method were conducted for developing an ANN model and finding the optimal input variables. In the first process, the initial ANN model was intuitively determined to have input neurons that seemed to have a relationship with the output neuron. The second process was conducted for finding the statistical relationship between the initial input variables and output variable. Result: Based on the statistical analysis, the optimal input variables were determined.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.634-647
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• 2019

The purpose of this study was to investigate the influence of constructive factors of predictive variables related to suicidal ideation, in contrast to previous studies analyzing the influence of predictive variables related to suicidal ideation. The 11,755 subjects were participated in the 12th(2017) KoWePS. After the diagnosis of multicollinearity among constructive factors of predictive variables related to suicidal ideation, and are analyzed with the statistical program Spss 23.0 as a calling logistic regression. The major findings were as follows: The more patriarchal gender role increase, the more language violence occur, the more feel loneliness, the more people treat me cold, the more drinking' black-out occur, the odds ratio of suicidal ideation increases, while the more ladder score of life increase, the odds ratio of suicidal ideation decreases. Based on this result, we suggests social welfare implications to reduce or prevent suicidal ideation, and the limitations of this study and the suggestions for future studies were also presented.

• Korean Journal of Child Studies
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• v.8 no.2
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• pp.17-44
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• 1987

The study examined the characteristics of the relationship of home environment variables and children's social development. Two studies were conducted ; Study I examined (1) the correlation of home environment variables and children's social ability and (2) the predictability of home environment variables for children's social ability by children's age. Study II investigated the causal relationship among the variables which are supposed to affect children's social ability. The subjects of this study were 240 children at age four, six and eight attending nursery schools, kindergartens and elementary schools and their mothers. Instruments included the Inventory of Home Stimulation (HOME), the Inventory of Sociodemographic Variables, social maturation scale, and the social-emotional developmental rating scale. The results obtained from this study were as follows : 1) Home environment variables had a positive correlation with children's social development at age four and six, but at age eight, only HOME variables had a significant positive correlation with children's social development. 2) The home environmental variables that significantly predicted children's social development differed according to children's age. That is, play materials, economic status of the home, and parent education were predictive of children's social development at age four, while parent's education, fostering maturity and independence, and play materials were predictive at age six. Fostering maturity and independence, aspects of physical environment, and economic status of the home were predictive at age eight. 3) The causal model of home environment effect on children's social development was formulated by exogenous variables (parent education and economic status of the home) and endogenous variables (direct stimulation, indirect stimulation and the emotional climate of the home). 4) The results of the analysis of the causal model showed that the variables that have a direct effect on children's social development differed according to children's age. That is, direct stimulation had more effect on children's social development at earlier ages, and indirect stimulation had more effect on children's social development at later ages. Among socio-demographic variables, parent's education was most closely related to children's social development. The amount of variance that explained children's social development decreased with increase in children's age.

• Health Policy and Management
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• v.9 no.2
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• pp.1-20
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• 1999

This study was conducted to investigate the predictors of hospital bankruptcy in Korea and to examine the predictive power for 3 types of statistical models of hospital bankruptcy. Data on 17 financial and 4 non-financial indicators of 30 bankrupt and 30 profitable hospitals in 1. 2, and 3 years before bankruptcy were obtained from the hospital performance databank of Korea Institute of Health Services Management. Significant variables were identified through mean comparison of each indicator between bankrupt and profitable hospitals, and the predictive power of statistical models of hospital bankruptcy were compared. The major findings are as follows. 1. Nine out of 21 indicators - fixed ratio, quick ratio, operating profit to total assets, operating profit to gross revenue, normal profit to total assets,normal profit to gross revenue, net profit to gross revenue, inventories turnrounds, and added value per adjusted patient - were found to be significantly predictitive variables in Logit and Probit models. 2. The predicdtive power of discriminant model of hospital bankruptcy in 1. 2, and 3 years before bankruptcy were 85.4, 79.0, and 83.8% respectively. With regard to the predictive power of the Logit model of hospital bankruptcy, they were 82.3, 75.8, and 80.6% respectively, and of the Probit model. 87.1. 80.6, and 88.7% respectively. 3. The predictive power of the Probit model of hospital bankruptcy is better than the other two predictive models.

• Korean Journal of Child Studies
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• v.8 no.1
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• pp.83-112
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• 1987

This study examined the characteristics of the relationship of home environment variables and children's intellectual ability. Two studies were conducted: Study I examined the predictability of home environment variables for children's intellectual ability by children's age and the correlations between environment variables and children's intellectual ability. Study II investigated causal relationships among the variables which are supposed to affect children's intellectual ability. The subjects of this study were 240 children at age four, six and eight attending nursery schools, kindergartens and elementary schools and their mothers. Instruments included the Inventory of Home Stimulation (HOME), inventory of sociodemographic variables, and the K-Binet scale. The results obtained from this study were as follows: 1) Home environment variables had a significant positive correlation (.36 ~ .78) with children's intellectual ability. 2) The home environmental variables that significantly predicted children's intellectual ability differed according to children's age. That is, play materials, breadth of experience, and quality of language environment were predictive of children's intellectual ability at age four, while parent's education, developmental stimulation, and play materials were predictive at age six. Economic status of the home, need gratification, avoidance of restriction, and emotional climate were predictive at age eight. 3) The causal model of home environment affecting children's intellectual ability was formulated by exogenous variables (parent education and economic status of the home) and by endogenous variables (direct stimulation, indirect stimulation and the emotional climate of the home). 4) The results of the analysis of the causal model showed that the kind of variables that affected children's intellectual ability directly differed according to children's age. That is, direct stimulation and parent's education affected children's intellectual ability directly at age four and six, while the economic status of the home and indirect stimulation affected intellectual ability directly at age eight. The amount of variance that explained children's intellectual ability increased with increase in children's age.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.