• Journal of Korean Society of Transportation
• /
• v.22 no.3 s.74
• /
• pp.27-39
• /
• 2004

The previous studies on analyzing the effects of traffic safety policies are very limited. Implementing traffic safety policies in view of their own urban traffic characteristics would be fairly desirable to handle properly the traffic safety problems. The relationships between traffic accidents and traffic safety policies have been researched by classifying the eighty one cities in Korea into four groups in terms of the size of the city population. Statistical analysis have been conducted for traffic accidents data and traffic safety policies, respectively. In order to mearsure the effectiveness of the traffic policies in the real world, regression models have been developed by handling the accident data and policy data. As a result of analysing the data, the traffic policies have showed different effects according to the size of the cities. While budget investment policies had provided enormous influences to reduce traffic accidents in the big cities more than a half million polulation, traffic enforcement and traffic education have been so efficient to control traffic accident problems in the smaller cities less than a half million poluation.

• The Korean Journal of Applied Statistics
• /
• v.21 no.1
• /
• pp.141-149
• /
• 2008

Recently we frequently analyze multivariate data with quite large number of variables. In such data sets, virtually duplicated variables may exist simultaneously even though they are conceptually distinguishable. Duplicate variables may cause problems such as the distortion of principal axes in principal component analysis and factor analysis and the distortion of the distances between observations, i.e. the input for cluster analysis. Also in supervised learning or regression analysis, duplicated explanatory variables often cause the instability of fitted models. Since real data analyses are aimed often at multiple purposes, it is necessary to reduce the number of variables to a parsimonious level. The aim of this paper is to propose a practical algorithm for selection of a subset of variables from a given set of p input variables, by the criterion of minimum trace of partial variances of unselected variables unexplained by selected variables. The usefulness of proposed method is demonstrated in visualizing the relationship between selected and unselected variables, in building a predictive model with very large number of independent variables, and in reducing the number of variables and purging/merging categories in categorical data.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.9
• /
• pp.243-251
• /
• 2022

In this paper, we propose a phenomenon that analyze the impact of market sentiment on China's real estate market through the perspective of behavioral economics. Previously, real estate market analyzation basically focus on some fundamental principles which include market price, monetary policies and income, etc. However, little research has explored market sentiment and its influence. By using principal components analysis (PCA), this study first creates buyer's sentiment and seller's sentiment to measure the heat of China's real estate market. Different from using traditional estimation method, the vector autoregressive model (VAR) is used to analyze how both sentiments affect real estate return. The overall results show that from unit root test and impulse response analyzation, the impact of seller's sentiment is positive to real estate market while buyer's sentiment is negative. At the same time, the higher seller's sentiment will have different influence on the housing market compared with the higher buyer's sentiment.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.6
• /
• pp.1501-1509
• /
• 2017

Wins above replacement (WAR) is the most commonly used statistics of the sabermetrics that measure baseball players' abilities. The advantage of a WAR is that it enables to compare performances of players even though they have different roles such as pitcher and hitter. However, WAR is difficult to obtain with common records. Thus, a past studies (Lee and Kim, 2016) suggested the batting ability index to determine the ability of the batter focused on the sabermetrics statistics WAR. In this paper, we selected the best hitter with applying Korea baseball 2016 data based on a proposed model and then observed a total raking of others according to BAI. We are assured that BAI is very excellent statistics through comparing BAI and WAR which is in the spotlight in evaluating performances of players.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.9
• /
• pp.3900-3914
• /
• 2012

This study examined the background of the recent global financial crisis and the concept of one of the financial derivatives such as the credit default swap(CDS) or synthetic CDO(collateral debt obligations), given the rapid growing and changing the over-the-counter derivative markets in their volume and structures. In comparison with the previous literature such as the study of Park & Kim (2011), this research empirically performed more thorough and comprehensive investigations to find any financial characteristics or attributes to determine the CDS spreads. Regarding the results obtained from the multiple regression models, the explanatory variables such as STYIELD3, SLOPE, INASSETS, and VOLATILITY, showed their statistically significant effects on all the tested dependent variables(DVs). Another procedure such as the principle component analysis(PCA), was also performed to account for additional IDVs as possible determinants of the dependent variables. Subsequent to this analysis, larger coefficients of each corresponding eigenvector such as BETA, PFT2, GROWTH, STD, and BLEVERAGE were found to be possible financial determinants. For robustness, all the IDVs were employed to be tested in the 'full' regression model with stepwise procedure. As a result, STYIELD3, SLOPE, and VOLATILITY, and BETA showed their statistically significant relationship with all the dependent variables of the CDS spreads.

• Journal of the Korean Geotechnical Society
• /
• v.36 no.6
• /
• pp.5-15
• /
• 2020

This study deals with the use of porewater pressure transducers to evaluate the stability of a fill dam through the correlation between the porewater pressure and water level. As a result of performing principal component analysis on a total of eight porewater pressure transducers installed in the fill dam, they were distributed into three groups. It was found to be distributed as internal, external, and top based on seepage line in the dam body. The correlation coefficient between porewater pressures and water level in group A located inside the seepage line indicated 0.94 to 1.00 and they are showing a strong positive linear relationships. It indicates that maintenance of the dam is required by the porewater pressure transducers of the group A. In addition, a linear regression analysis was performed with the determination coefficients of the group A of 0.89 to 0.99. It was found that the pore water pressure can be predicted and the stability of the dam can be evaluated by comparing it with the currently measured values when the water level is fixed as an explanatory variable.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.5
• /
• pp.95-101
• /
• 2008

Modeling of stock prices forecast has been considered as one of the most difficult problem to develop accurately since stock prices are highly correlated with various environmental conditions including economics and political situation. In this paper, we propose a agent system approach to predict Korea Composite Stock Price Index (KOSPI) using neural network and statistical methods. To minimize mean of prediction error and variation of prediction error, agent system includes sub-agent modules for feature extraction, variables selection, forecast engine selection, and forecasting results analysis. As a first step to develop agent system for KOSPI forecasting, twelve economic indices are selected from twenty two basic standard economic indices using principal component analysis. From selected twelve economic indices, prediction model input variables are chosen again using best-subsets regression method. Two different types data are tested for KOSPI forecasting and the Prediction results showed 11.92 points of root mean squared error for consecutive thirty days of prediction. Also, it is shown that proposed agent system approach for KOSPI forecast is effective since required types and numbers of prediction variables are time-varying, so adaptable selection of modeling inputs and prediction engine are essential for reliable and accurate forecast model.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.7
• /
• pp.625-637
• /
• 2020

In order to decide the naval ship weapon system acquisition for national policy/market economy activities, the decision makers can determine policy based on current technology level/concentration/utilization. For this, the decision makers apply the major common technology field analysis using patents data. As a method for collecting patent data, we can collect patent data of domestic mobile carriers through the Korea Intellectual Property Rights Information System of Korean Intellectual Property Office. As a result, we collected 14,964 patents/352 International Patent Classification(IPC) types. Based on these data, we performed three analysis processes (SNA, PCA, ARIMA, Text Mining) and got each result from extracting 58 IPC types of SNA and 7 IPC types of PCA. Based on the analysis results, we have confirmed that 7 IPC(B63B, H01M, F03D, B01D, H02K, B23K, H01H) types are the Major Common Technology Distribution of domestic Defense Companies.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.5
• /
• pp.723-737
• /
• 2017

In order to decide the national technical standards policy for national policy/market economy activities, the people in charge commonly make policy decisions based on the current technology level/concentration/utilization by means of major common technology field analysis using patent data. One possible source of such patent data is the domestic mobile carriers through the Korea Intellectual Property Rights Information System (KIPRIS) of the Korean Intellectual Property Office (KIPO). Using this system, we collected 20,294 patents and 152 International Patent Classification (IPC) types and confirmed KTs (9,738 cases / 47.98%), which perform relatively high technology retention activities compared to other mobile carriers through the KIPRIS of KIPO. Based on these data, we performed three analyses (SNA, PCA, ARIMA) and extracted 30 IPC types from the SNA and 4 IPC types from the PCA. Based on the above analysis results, we confirmed that 4 IPC (H04W, H04B, G06Q, H04L) types are the major common technology field of the domestic mobile carriers. Finally, the number of 4 IPC (H04W, H04B, G06Q, H04L) forecast averages of the ARIMA forecast result is lower than the number of existing time series patent data averages.

• Journal of Korean Society of Transportation
• /
• v.24 no.7 s.93
• /
• pp.15-25
• /
• 2006

This study was to investigate the impact of region-wide travel pattern on local fiscal capacity in the Seoul metropolitan area. The study adopted both factor analysis and regression modeling for it, while using fiscal-and travel-related variables as well as urban characteristics determining travel patterns. We used the former method to compress independent variables of travel and urban characteristics because of strong correlationship between them. Four factors identified by the analysis output were adopted in regression models with some dependent variables representing local fiscal capacity. Their results resulting from both analyses showed that local fiscal inequality within the metropolitan area is driven by region-wide travel Patterns such as total trips. inner trip ratio, and the ratio of trips from and to the Seoul city.