Browse > Article
http://dx.doi.org/10.7837/kosomes.2013.19.6.612

A Forecast Method of Marine Traffic Volume through Time Series Analysis  

Yoo, Sang-Rok (Graduate school of Mokpo National Maritime University)
Park, Young-Soo (Korea Maritime University)
Jeong, Jung-Sik (Mokpo National Maritime University)
Kim, Chul-Seong (Mokpo National Maritime University)
Jeong, Jae-Yong (Mokpo National Maritime University)
Publication Information
Journal of the Korean Society of Marine Environment & Safety / v.19, no.6, 2013 , pp. 612-620 More about this Journal
Abstract
In this study, time series analysis was tried, which is widely applied to demand forecast of diverse fields such as finance, economy, trade, and so on, different from previous regression analysis. Future marine traffic volume was forecasted on the basis of data of the number of ships entering Incheon port from January 1996 to June 2013, through courses of stationarity verification, model identification, coefficient estimation, and diagnostic checking. As a result of prediction January 2014 to December 2015, February has less traffic volume than other months, but January has more traffic volume than other months. Also, it was found out that Incheon port was more proper to ARIMA model than exponential smoothing method and there was a difference of monthly traffic volume according to seasons. The study has a meaning in that future traffic volume was forecasted per month with time series model. Also, it is judged that forecast of future marine traffic volume through time series model will be the more suitable model than prediction of marine traffic volume with previous regression analysis.
Keywords
Time series analysis; ARIMA model; Exponential smoothing method; Forecast of future marine traffic volume; Regression analysis;
Citations & Related Records
Times Cited By KSCI : 10  (Citation Analysis)
연도 인용수 순위
1 Kim, J. H.(2007), The Estimation of Future Container Ship Traffic for Three Major Ports in Korea, Journal of Korean Navigation and Port Research, Vol. 31, No. 5, pp. 353-359.   과학기술학회마을   DOI   ScienceOn
2 Mo, S. W.(2010), Forecasts of the 2011-BDI Using the ARIMA Type Models, Journal of Korea Port Economic Association, Vol. 26, No. 4, pp. 207-218.   과학기술학회마을
3 Mo, S. W.(2013), A Forecast of Shipping Business during the Year of 2013, Journal of Korea Port Economic Association, Vol. 29, No. 1, pp. 67-76.   과학기술학회마을
4 Shin, C. H. and S. H. Jeong(2011), A Study on Application of ARIMA and Neural Networks for Time Series Forecasting of Port Traffic, Journal of Navigation and Port Research, Vol. 35, No. 1, pp. 83-91.   과학기술학회마을   DOI   ScienceOn
5 Kim, J. H., S. G. Gug and S. W. Kim(2007), Estimation on the Future Traffic Volumes and Analysis on Information Value of Tidal Current Singnal in Incheon, Journal of Korea Navigation and Port Research, Vol. 31, No. 6, pp. 456-462.   과학기술학회마을   DOI   ScienceOn
6 Kim, J. H.(2008a), The Forecast of the Cargo Transportation and Traffic Volume on Container in Gwangyang Port using Time Series Models, Journal of Navigation and Port Research, Vol. 32, No. 6, pp. 425-431.   과학기술학회마을   DOI   ScienceOn
7 Kim, J. H.(2008b), The Forecast of the Cargo Transportation for the North Port in Busan using Time Series Models, Journal of Korea Port Economic Association, Vol. 24, No. 2, pp. 1-17.   과학기술학회마을
8 Koo, J. Y.(1997), Evaluation of Traffic Congestion in Channels within Harbour Limit, Journal of Port and Harbor Research, Vol. 11, No. 2, pp. 173-189.   과학기술학회마을
9 Lee, Y. S. and Y. J. Ahn(2013), A Study on the Standard Ship's Length of Domestic Trade Port, Journal of the Korean Society of Marine Environment & Safety, Vol. 19, No. 2, pp. 164-170.   과학기술학회마을   DOI   ScienceOn
10 Mo, S. W.(2012), The Behavioral Analysis of the Trading Volumes of Gwangyang Port: Comparison with Incheon and Pyeongtaek-Dangjin Port, Journal of Korea Port Economic Association, Vol. 28, No. 3, pp. 111-125.   과학기술학회마을
11 Park, S. B., J. W. Kim, S. I. Jeon, C. U. Kim, E. J. Choi, C. H. Lee and Y. S. Heo(2012), An Effective Demand Forecasting and Its Applications, Samsung Economic Research Institute, Reserch Report, pp. 24-26.
12 Stein, R. and P. Shaman(1989), A Fixed Point Characterization for Bias of Auto-Regressive Estimators, The Analysis of Statistics, Vol. 17, No. 3, pp. 1275-1284.
13 Kim, J. H., S. G. Gug and M. C. Kim(2006), Estimation on the Future Traffic Volumes and Analysis on Crossing Situation Risk for Gamcheon Harbor, Journal of Korea Navigation and Port Research, Vol. 30, No. 8, pp. 617-622.   과학기술학회마을   DOI   ScienceOn
14 Shin, C. H., J. S. Kang, S. N. Park and J. H. Lee(2008), A Study on the Forecast of Port Traffic using Hybrid ARIMA-Neural Network Model, Journal of Navigation and Port Research, Vol. 32, No. 1, pp. 81-88.   과학기술학회마을   DOI   ScienceOn
15 Yeo, G. T., H. G. Lee, S. M. Soak and C. Y. Lee(1998), A Simulation Study on the Marine Traffic Congestion in Pusan Port, Journal of Port and Harbor Research, Vol. 9, pp. 1-17.   과학기술학회마을
16 Box, G. E. P., G. M. Jenkins and G. C. Reinsel(2008), Time Series Analysis: Forecasting and Control, A John Wiley and Sons Inc., pp. 79-86, pp. 103-113.
17 Fujii, Y., M. Tsutomu and H. Kiyosshi(1981), Marine Traffic Engineering, Haemoondang, pp. 12-13, p. 45.