• Journal of Korea Port Economic Association
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• v.28 no.3
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• pp.111-125
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• 2012

This study investigates the behavioral characteristic difference of the container volumes of three ports-Gwangyang, Incheon, and Pyeongtaek-Dangjin. All series span the period January 2003 to December 2011. I first test whether the series are stationary or not. I can reject the null hypothesis of a unit root in each of the level variables and of a unit root for the residuals from the cointegration at the 5 percent significance level. I hitherto make use of error-correction model and find that Gwangyang port is the slowest in adjusting the short-run disequilibrium, whereas the adjustment speed of Incheon is much faster than that of Gwangyang. The impulse response functions indicate that container volumes increase only a little to the negative shocks in exchange rate, while they respond positively to the shocks in the business activity in a great magnitude and decay very slowly to its pre-shock level. meaning that the shocks last very long. The accumulative response to the exchange rate increase of 20 won per dollar and the 5 point industrial production increase is the smallest in Gwangyang, no more than a half of that of two ports. The intervention-ARIMA models also forecast that Gwangyang port will have much lower growth rate than Incheon and Pyeongtaek-Dangjin port in trading volumes.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.7-14
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• 2020

This study analyzed the effect of the number of deaths of circulatory system diseases according to 12-day short-term exposure of carbon monoxide from January 2010 to December 2018, and predicted the future treatment cost of circulatory system diseases according to increased carbon monoxide concentration. Data were extracted from Air Korea of Korea Environment Corporation and Korea Statistical Office, and analyzed using Poisson regression analysis and ARIMA intervention model. For statistical processing, SPSS Ver. 21.0 program was used. The results of the study are as follows. First, as a result of analyzing the relationship between the impact of short-term carbon monoxide exposure on death of circulatory system diseases from the day to the previous 11 days, it was found that the previous 11 days had the highest impact. Second, with the increase in carbon monoxide concentration, the future circulatory system disease treatment cost was estimated at 10,123 billion won in 2019, higher than the observed value of 9,443 billion won at the end of December 2018. In addition, when summarized by month, it can be seen that the cost of treatment for circulatory diseases increases from January to December, reflecting seasonal fluctuations. Through such research, the future for a healthy life for all citizens can be realized by distributing various devices and equipment utilizing IoT to preemptively respond to the increase in air pollutants such as carbon monoxide.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.4
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• pp.77-89
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• 2013

The purpose of this study is to anticipate the air travel demands over the period of 164 months, from January 1997 to August 2010 using ARIMA-Intervention modeling on the selected sample data. The sample data is composed of the number of the passengers who in the domestic route for Jeju route. In the analysis work of this study, the past events which are assumed to have affected the demands for the air travel routes to Jeju in different periods were used as the intervention variables. The impacts of such variables were reflected in the presupposed demand. The intervention variables used in this study are, respectively, the World Cup event in 2002 (from May to June), 2003 SARS outbreak (from April to May), Tsunami in January 2005, and the influenza outbreak from October to December 2009. The result of the above mentioned analysis revealed that the negative intervention events, like a global outbreak of an epidemic did have negative impact on the air travel demands in a risk aversion by the users of the aviation services. However, in case of the negative intervention events in limited area, where there are possible substituting destinations for the tourists, the impact was positive in terms of the air travel demands for substituting destinations due to the rational expectation of the users as they searched for other options. Also in this study, it was discovered that there is not a binding correlation between a nation wide mega-event, such as the World Cup games in 2002, and the increased air travel demands over a short-term period.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.64-71
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• 2002

This research developed construction cost forecasting model using Building Construction Cost Index, time series analysis and Artificial Neural Networks. By this model, we could calculate the forecasted values of construction cost precisely and efficiently. And we also could find out that the standard deviation of forecasted values is 0.375 and it is a very exact result, so the standard deviation is just 0.33 percent of 112.28, the average of Building Construction Cost Index. And it show more exact forecasting result in comparison with Time Series Analysis.

• Korean Journal of Environmental Biology
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• v.34 no.4
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• pp.365-373
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• 2016

Much of the data used in the analysis of environmental ecological data is being obtained over time. If the number of time points is small, the data will not be given enough information, so repeated measurements or multiple survey points data should be used to perform a comprehensive analysis. The method used for that case is longitudinal data analysis or mixed model analysis. However, if the amount of information is sufficient due to the large number of time points, repetitive data are not needed and these data are analyzed using time series analysis technique. In particular, with a large number of data points in the current situation, when we want to predict how each variable affects each other, or what trends will be expected in the future, we should analyze the data using time series analysis techniques. In this study, we introduce univariate time series analysis, intervention time series model, transfer function model, and multivariate time series model and review research papers studied in Korea. We also introduce an error correction model, which can be used to analyze environmental ecological data.