• Title/Summary/Keyword: Multiple Regression Analysis with Dummy Variable

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Price Monitoring Automation with Marketing Forecasting Methods

  • Oksana Penkova;Oleksandr Zakharchuk;Ivan Blahun;Alina Berher;Veronika Nechytailo;Andrii Kharenko
    • International Journal of Computer Science & Network Security
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    • v.23 no.9
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    • pp.37-46
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    • 2023
  • The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

Model on the Suitable Illuminance at Urban Neighborhood Park (도시근린공원의 적정조도모형)

  • 최연철;김진선
    • Journal of the Korean Institute of Landscape Architecture
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    • v.29 no.3
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    • pp.29-37
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    • 2001
  • The purpose of this study is to determine the suitable illuminance model of an urban neighborhood park. To this end, 1 dependent variable and 11 independent variables were set, and multiple regression analysis was applied to find correlation between variables and the model. The results of this study are as follows; 1) Among 11 independent variables abstracted to study suitable illuminance model of an urban neighborhood park, as a result of analysis on correlation between suitable illuminance of a dependent variable and activity space by using dummy variables, activity type and illuminance by spaces the suitable illuminance required for an urban neighborhood park was much influenced by activity type, and the fact that the activity was not limited to a specific space. 2) As a result of multiple regression analysis, independent variables influencing the suitable illuminance model of an urban neighborhood park were activity space, illuminance by spaces, seated activity, standing activity, and sporting activity. And, for relative contribution of independent variables to suitable illuminance, activity with sporting showed an importance 22 times higher than seated activity. When the central square(Sp_1) of activity spaces was set to reference category using dummy variables, it showed a contribution 52 times higher than sorting space(Sp_7) and the central square as the most important variable. 3) It was analyzed that suitable illuminance of an urban neighborhood part was most influenced by sporting activity but the relative contribution of a sporting space where activity with sporting occurs was least in view of the function of the space. Very high illuminance is required to accept high activity, and if illuminance at a certain space becomes too high, it may influence the illuminance of other spaces, and may consequently have a negative effect on the suitable illuminance of an urban neighborhood park. The results of this study were mainly for teenagers and young adults in their twenties, so further concrete studies which consider gender and a wider age range are needed in the future. Based on subsequent study, suitable illuminance by spaces shall be suggested.

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Models for Estimating Yield of Italian Ryegrass in South Areas of Korean Peninsula and Jeju Island

  • Peng, Jing Lun;Kim, Moon Ju;Kim, Byong Wan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.36 no.3
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    • pp.223-236
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    • 2016
  • The objective of this study was to construct Italian ryegrass (IRG) dry matter yield (DMY) estimation models in South Korea based on climatic data by locations. Obviously, the climatic environment of Jeju Island has great differences with Korean Peninsula. Meanwhile, many data points were from Jeju Island in the prepared data set. Statistically significant differences in both DMY values and climatic variables were observed between south areas of Korean Peninsula and Jeju Island. Therefore, the estimation models were constructed separately for south areas of Korean Peninsula and Jeju Island separately. For south areas of Korean Peninsula, a data set with a sample size of 933 during 26 years was used. Four optimal climatic variables were selected through a stepwise approach of multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the selected four climatic variables and cultivated locations as dummy variables was constructed. The model could explain 37.7% of the variations in DMY of IRG in south areas of Korean Peninsula. For Jeju Island, a data set containing 130 data points during 17 years were used in the modeling construction via the stepwise approach of multiple regression analysis. The model constructed in this research could explain 51.0% of the variations in DMY of IRG. For the two models, homoscedasticity and the assumption that the mean of the residuals were equal to zero were satisfied. Meanwhile, the fitness of both models was good based on most scatters of predicted DMY values fell within the 95% confidence interval.

The Effect of Urban and Climate Characteristics on Energy Resilience - Focusing on Blackout Time - (도시 및 기후특성이 에너지 회복력에 미치는 영향 - 정전발생시간을 중심으로 -)

  • Lee, DongSung;Moon, Tae-Hoon
    • Journal of Korea Planning Association
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    • v.54 no.4
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    • pp.122-130
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    • 2019
  • The purpose of this study is to analyze effect of climate and urban factors on energy resilience, and to explore policy alternatives to strengthen resilience of energy system. For this purpose, this study used extensive literature review on resilience studies and multiple regression analysis. In this study, blackout time was set as a dependent variable. And the independent variables were divided into climate and urban (robustness, countermeasure capacity) characteristics. As a result of the analysis, in terms of climate characteristics, maximum wind speed and cooling/heating degree-day have statistically significant impact on blackout time. With regard to urban characteristics, number of consumer, ratio of deteriorated housing and coast dummy variables have statistically significant impact on blackout time. And the ratio of government employees and road ratio were found to be the most influencing factors to shorten time taken to restore original level of electricity supply. Based on the study results, several policy suggestions to improve energy resilience were made such as continuous management of vulnerable areas and strengthening disaster response services. This study only considered engineering dimension of resilience. Further studies need to be approached on ecological & social-ecological dimension.

A Yield Estimation Model of Forage Rye Based on Climate Data by Locations in South Korea Using General Linear Model

  • Peng, Jing Lun;Kim, Moon Ju;Kim, Byong Wan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.36 no.3
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    • pp.205-214
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    • 2016
  • The objective of this study was to construct a forage rye (FR) dry matter yield (DMY) estimation model based on climate data by locations in South Korea. The data set (n = 549) during 29 years were used. Six optimal climatic variables were selected through stepwise multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the six climatic variables and cultivated locations as dummy variables was constructed as follows: DMY = 104.166SGD + 1.454AAT + 147.863MTJ + 59.183PAT150 - 4.693SRF + 45.106SRD - 5230.001 + Location, where SGD was spring growing days, AAT was autumnal accumulated temperature, MTJ was mean temperature in January, PAT150 was period to accumulated temperature 150, SRF was spring rainfall, and SRD was spring rainfall days. The model constructed in this research could explain 24.4 % of the variations in DMY of FR. The homoscedasticity and the assumption that the mean of the residuals were equal to zero was satisfied. The goodness-of-fit of the model was proper based on most scatters of the predicted DMY values fell within the 95% confidence interval.

Development of Fire Engine Travel Time Estimation Model for Securing Golden Time (골든타임 확보를 위한 소방차 통행시간 예측모형 개발)

  • Jang, Ki-hun;Cho, Seong-Beom;Cho, Yong-Sung;Son, Seung-neo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.1-13
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    • 2020
  • In the event of fire, it is necessary to put out the fire within a golden time to minimize personal and property damages. To this end, it is necessary for fire engines to arrive at the site quickly. This study established a fire engine travel time estimation model to secure the golden time by identifying road and environmental factors that influence fire engine travel time in the case of fire by examining data on fire occurrence with GIS DB. The study model for the estimation of fire engine travel time (model 1) covers variables by applying correlation analysis and regression analysis with dummy variables and predicts travel time for different types of places where fire may occur (models 2, 3, 4). Analysis results showed that 17 siginificant independent variables are derived in model 1 and the fire engine travel time differs depending on the types of places where fire occurs. Key variables(travel distance, number of lane, type of road) that are included commonly in the 4 models were identified. Variables identified in this study can be utilized as indicators for research related to travel time of emergency vehicles and contribute to securing the golden time for emergency vehicles.

Development of Freeway Incident Duration Prediction Models (고속도로 돌발상황 지속시간 예측모형 개발)

  • 신치현;김정훈
    • Journal of Korean Society of Transportation
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    • v.20 no.3
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    • pp.17-30
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    • 2002
  • Incident duration prediction is one of the most important steps of the overall incident management process. An accurate and reliable estimate of the incident duration can be the main difference between an effective incident management operation and an unacceptable one since, without the knowledge of such time durations, traffic impact can not be estimated or calculated. This research presents several multiple linear regression models for incident duration prediction using data consisting of 384 incident cases. The main source of various incident cases was the Traffic Incident Reports filled out by the Motorist Assistant Units of the Korea Highway Corporation. The models were proposed separately according to the time of day(daytime vs. nighttime) and the fatality/injury incurred (fatality/injury vs. property damage only). Two models using an integrated dataset, one with an intercept and the other without it, were also calibrated and proposed for the generality of model application. Some findings are as follows ; ?Variables such as vehicle turnover, load spills, the number of heavy vehicles involved and the number of blocked lanes were found to significantly affect incident duration times. ?Models, however, tend to overestimate the duration times when a dummy variable, load spill, is used. It was simply because several of load spill incidents had excessively long clearance times. The precision was improved when load spills were further categorized into "small spills" and "large spills" based on the size of vehicles involved. ?Variables such as the number of vehicles involved and the number of blocked lanes found not significant when a regression model was calibrated with an intercept. whereas excluding the intercept from the model structure signifies those variables in a statistical sense.

A Study on the Age Distribution Factors of One Person Household in Seoul using Multiple Regression Analysis (다중회귀분석을 이용한 서울시 1인 가구의 연령별 분포요인에 관한 연구)

  • Lee, SunHee;Yoon, DongHyeun;Koh, JuneHwan
    • Spatial Information Research
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    • v.23 no.3
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    • pp.11-21
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    • 2015
  • While the number of total population in Seoul has been on the constant decline for the last few years, the number of household has increased due to the rising tendency of the smaller households. In 2010, the small households in the metropolitan areas accounted for 44% of the entire households, and Statistics Korea has reported that one person household, which will take up more than 30% of the whole household, will have been the most common type of household by 2020. This reason of rise will be differently shown according to age like the preferred housing type or surrounding environments, this research is suggest to research hypothesis that distinction of age leads to the spatial distribution of one person household. Therefore, this research is to exercise a multiple regression analysis targeting on the facilities, which become the spatial distribution factor of one person household, with the independent variable gained from the concluded area calculated with the area ratio of the spatial unit followed by the service area analysis based on network. The spatial unit is the census output of Seoul, and based on this the interaction between the number of one person household according to age and the factors of its distribution. Also, the spatial regions - downtown, northeast, southeast, northwest, southwest - are designed as dummy variables and the results of each region are found out. As a result, the spatial regions occupied according to age are found to be varied - people in their 20s prefer housings near the college, 30s lease or the monthly rental housings, 40s the monthly rental housings, and over 60s the housing with the floor area of less than $40m^2$. Likewise, one person household has different types of housing environments preferred according to age, and thus a housing policy concerning this will have to be suggested.

The Study on Improving Medical Care Service by Analyzing the Time While the Homeless Patients Length of Stay Emergency Medical Institution (행려환자의 응급의료기관 체류시간 분석을 통한 의료서비스 개선방안에 대한 연구)

  • Lee, Jin-Woo;Kim, Kwang-Hwan
    • Journal of Digital Convergence
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    • v.11 no.10
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    • pp.619-627
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    • 2013
  • This study reviews the time while the homeless patients Length of Stay emergency medical institution according to their medical treatment when they visit a hospital and characteristics of pathogenesis to understand the related factors affecting the case. Such review aims at providing basic data and information on how to improve medical care services of our society. 691 homeless patients visited an emergency medical care institution in Chungnam-si for one year from January 1, 2012 until December 31, of the same year were surveyed. Methods adopted were the analysis of frequency, ANOVA, correlation analysis and multiple regression analysis was conducted by making an independent variable as a dummy. This study came to a conclusion that first of all a medical care institution is required to avoid negative awareness and it should provide the homeless patients with medical care of better quality, having emergency care support system. Second, as most of the homeless patients are in their 40 or 50's, they are still in the age of high productivity of our society. Therefore, proper policy should be established and managed by the government on the program for their returning to the society as well as providing them with better medical care and support.

Analysis on Factors Influencing Welfare Spending of Local Authority : Implementing the Detailed Data Extracted from the Social Security Information System (지방자치단체 자체 복지사업 지출 영향요인 분석 : 사회보장정보시스템을 통한 접근)

  • Kim, Kyoung-June;Ham, Young-Jin;Lee, Ki-Dong
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.141-156
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    • 2013
  • Researchers in welfare services of local government in Korea have rather been on isolated issues as disables, childcare, aging phenomenon, etc. (Kang, 2004; Jung et al., 2009). Lately, local officials, yet, realize that they need more comprehensive welfare services for all residents, not just for above-mentioned focused groups. Still cases dealt with focused group approach have been a main research stream due to various reason(Jung et al., 2009; Lee, 2009; Jang, 2011). Social Security Information System is an information system that comprehensively manages 292 welfare benefits provided by 17 ministries and 40 thousand welfare services provided by 230 local authorities in Korea. The purpose of the system is to improve efficiency of social welfare delivery process. The study of local government expenditure has been on the rise over the last few decades after the restarting the local autonomy, but these studies have limitations on data collection. Measurement of a local government's welfare efforts(spending) has been primarily on expenditures or budget for an individual, set aside for welfare. This practice of using monetary value for an individual as a "proxy value" for welfare effort(spending) is based on the assumption that expenditure is directly linked to welfare efforts(Lee et al., 2007). This expenditure/budget approach commonly uses total welfare amount or percentage figure as dependent variables (Wildavsky, 1985; Lee et al., 2007; Kang, 2000). However, current practice of using actual amount being used or percentage figure as a dependent variable may have some limitation; since budget or expenditure is greatly influenced by the total budget of a local government, relying on such monetary value may create inflate or deflate the true "welfare effort" (Jang, 2012). In addition, government budget usually contain a large amount of administrative cost, i.e., salary, for local officials, which is highly unrelated to the actual welfare expenditure (Jang, 2011). This paper used local government welfare service data from the detailed data sets linked to the Social Security Information System. The purpose of this paper is to analyze the factors that affect social welfare spending of 230 local authorities in 2012. The paper applied multiple regression based model to analyze the pooled financial data from the system. Based on the regression analysis, the following factors affecting self-funded welfare spending were identified. In our research model, we use the welfare budget/total budget(%) of a local government as a true measurement for a local government's welfare effort(spending). Doing so, we exclude central government subsidies or support being used for local welfare service. It is because central government welfare support does not truly reflect the welfare efforts(spending) of a local. The dependent variable of this paper is the volume of the welfare spending and the independent variables of the model are comprised of three categories, in terms of socio-demographic perspectives, the local economy and the financial capacity of local government. This paper categorized local authorities into 3 groups, districts, and cities and suburb areas. The model used a dummy variable as the control variable (local political factor). This paper demonstrated that the volume of the welfare spending for the welfare services is commonly influenced by the ratio of welfare budget to total local budget, the population of infants, self-reliance ratio and the level of unemployment factor. Interestingly, the influential factors are different by the size of local government. Analysis of determinants of local government self-welfare spending, we found a significant effect of local Gov. Finance characteristic in degree of the local government's financial independence, financial independence rate, rate of social welfare budget, and regional economic in opening-to-application ratio, and sociology of population in rate of infants. The result means that local authorities should have differentiated welfare strategies according to their conditions and circumstances. There is a meaning that this paper has successfully proven the significant factors influencing welfare spending of local government in Korea.