• Journal of Information Processing Systems
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• v.18 no.6
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• pp.719-728
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• 2022

The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.471-477
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• 2017

This paper deals with the viewing rate trends of digital media service special reference to terrestrial real time broadcasting of IPTV. In a few years, TV viewership of young people is decreasing, the audience viewing rate of the terrestrial broadcasting which is the representative of the media decreases, and the change of the broadcasting industry is progressing. Especially after the terrestrial broadcaster 's VOD holdback was extended, the viewer' s movement on the competitive channel & mobile media was rapidly progressing. Researcher assumed that the viewing rate of the terrestrial real-time broadcasting has influenced the comprehensive channel, CJ E&M subsidiary channels. As a result, researcher verified using statistical methodological time series analysis and regression analysis. Based on these results, researcher expects media players to prepare policies for viewers' satisfaction and symbiotic growth of markets.

• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.617-629
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• 2005

In this paper, a hypothesis is tested that division of non-monotonic time series into monotonic parts will improve the estimation of trends through increased homogeneity in direction of time-variation using LOWESS smoothing and seasonal Kendall test. From the trend analysis of generated time series and water temperature, discharge, air temperature and solar radiation of Lake Daechung, it is shown that the hypothesis is supported by improved estimation of trends and slopes. Also, characteristics in homogeneity variation of seasonal changes seems to be more clearly manifested as homogeneity in direction of time-variation is increased. And this will help understand the effects of human intervention on natural processes and seems to warrant more in-depth study on this subject. The proposed method can be used for trend analysis to detect monotonic trends and it is expected to improve understanding of long-term changes in natural environment.

• Journal of the Korean Society of Safety
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• v.27 no.3
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• pp.141-146
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• 2012

This study deals with the accident model using panel data which are composed of time series data of 2005 through 2007 and cross sectional data of link sections in Cheongju. Panel data are repeatedly collected over time from the same sample. The purpose of the study is to develop the traffic accident model using the above panel data. In pursuing the above, this study gives particular attentions to deriving the optimal models among various models including TSCSREG (Time Series Cross Section Regression). The main results are as follows. First, 8 panel data models which explained the various effects of accidents were developed. Second, $R^2$ values of fixed effect models were analyzed to be higher than those of random effect models. Finally, such the variables as the sum of the number of crosswalk on intersections and sum of the number of intersections were analyzed to be positive to the accidents.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.169-193
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• 2013

This study investigates time series data on internet banking systems and business performances for 5 large-scale banks : Kookmin, Woori, Hana, City, Shinhan. These banks have the common features that they merged with other banks around 2000, hence they experienced massive IS integration between banks. This study adopted VAR and VECM for identifying Granger causality between the quality of internet banking systems and the performances of banks(operating revenue and cost). The main results are as follows. First, internet banking system impacts positively on the revenues as well as costs of banks. Second, the improvement of internet banking system is instigated by cost part more than revenue part. Hence, the results imply that banks tries to reduce operating costs via internet banking systems, however the systems rather increased the costs of banks, although the systems increased operating revenues of banks too.

• Journal of Digital Contents Society
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• v.19 no.3
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• pp.513-519
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• 2018

The objective of this study was to examine the trends on social network services. The abstracts of 308 articles were extracted from web of science database published between 1994 and 2016. Time series analysis and topic modeling of text mining were implemented. The topic modeling results showed that the research topics were mainly 20 topics: trust, support, satisfaction model, organization governance, mobile system, internet marketing, college student effect, opinion diffusion, customer, information privacy, health care, web collaboration, method, learning effectiveness, knowledge, individual theory, child support, algorithm, media participation, and context system. The time series regression results indicated that trust, support satisfaction model, and remains of the topics were hot topics. This study also provided suggestions for future research.

• Journal of Korea Water Resources Association
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• v.49 no.1
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• pp.1-9
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• 2016

A correlation analysis between raw water turbidity at two wide-area water treatment plants and hydrological data was conducted for efficient water supply, design and management of water treatment plant. Both correlation analysis and principal component analysis were conducted using hydrological time series data such as inflow discharge, outflow discharge, and rainfall at dam basin of intake station of wide-area water treatment plants. And, forecasting of change in turbidity was conducted using regression equation for turbidity prediction. The raw water turbidity of two water treatment plants was strongly related to time series of discharge. The raw water turbidity of Chungju water treatment plant is strongly related to outflow discharge at Chungju dam (0.708). Whereas, the raw water turbidity of Wabu water treatment plant is strongly related to inflow discharge at Paldang dam (0.805). Similar trends between turbidity forecasting result using regression equation and calculation result using estimation equation on Korea water supply facilities standard were obtained. The result of this study can provide basic data for construction and management of water treatment plant.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1177-1190
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• 2009

The traffic operating speed is one of important information to measure a road capacity. When we supply the information of the road of high traffic by using navigation, offering the present traffic information and the forecasted future information are the outstanding functions to serve the more accurate expected times and intervals. In this study, we proposed the traffic speed forecasting model using the accumulated traffic speed data of the road and highway and forecasted the average speed for each the road and high interval and each time interval using Fourier transformation and time series regression model with trigonometrical function. We also propose the proper method of missing data imputation and treatment for the outliers to raise an accuracy of the traffic speed forecasting and the speed grouping method for which data have similar traffic speed pattern to increase an efficiency of analysis.

• The Journal of Industrial Distribution & Business
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• v.10 no.9
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• pp.53-60
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• 2019

Purpose - The objective of this paper is to discover if there exists a relationship between the economic index and distribution industry index in Korean. Because of the distribution industry boom in the recent years, a lot of interest in the relationship between the economic index and distribution industry index in Korean and the economy has been generated. This article examine on the mutual influence between economic index and distribution industry index in Korean. Research design, data, and methodology - For this purpose, we use the vector-auto regression model, impulse response function and variance decomposition of the economic index and distribution industry index, Granger causality test using weekly data on the economic index and distribution industry price index in korea. The sample period is covering from January 2, 2010 to August 31, 2019. The VAR model can also be linked to cointegration analysis. Cointegration Analysis makes possible to find a mechanism causing x and y to move around a long-run equilibrium (Engle and Granger, 1987). This equilibrium means that external shocks may separate the series temporarily at any particular time, but there will be an overall tendency towards some type of long-run equilibrium. If variables are found to have this tendency they are said to be cointegrated and a long-run relationship between these series is established. These econometric tools have been applied widely into economics and business areas to analyze intertemporal linkages between different time series. Results - This research showed following main results. First, from the basic statistic analysis of the economic index and distribution industry index in Korean, the economic index and the distribution industry index in korea have unit roots. Second, there is at least one cointegration between the economic index and distribution industry index in Korean. Finally, the correlation between of the economic index and the distribution industry index in korea is (+) 0.528876. Conclusions - We find that the distribution industry price index Granger cause the economic index in korea. As a consequence, the distribution industry index affect the economic index in Korean. The distribution industry index to the economic index is stronger than that from the economic index to the distribution industry index.

• ETRI Journal
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• v.43 no.6
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• pp.1058-1080
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• 2021

Crime is not a completely random event but rather shows a pattern in space and time. Capturing the dynamic nature of crime patterns is a challenging task. Crime prediction models that rely only on neighborhood influence and demographic features might not be able to capture the dynamics of crime patterns, as demographic data collection does not occur frequently and is static. This work proposes a novel approach for crime count and hotspot prediction to capture the dynamic nature of crime patterns using taxi data along with historical crime and demographic data. The proposed approach predicts crime events in spatial units and classifies each of them into a hotspot category based on the number of crime events. Four models are proposed, which consider different covariates to select a set of independent variables. The experimental results show that the proposed combined subset model (CSM), in which static and dynamic aspects of crime are combined by employing the taxi dataset, is more accurate than the other models presented in this study.