Browse > Article
http://dx.doi.org/10.7837/kosomes.2014.20.1.033

A Prediction of Marine Traffic Volume using Artificial Neural Network and Time Series Analysis  

Yoo, Sang-Lok (Graduate school of Mokpo National Maritime University)
Kim, Jong-Su (Division of Marine System Engineering, Korea Maritime and Ocean University)
Jeong, Jung-Sik (Division of International Maritime Transportation Science, Mokpo National Maritime University)
Jeong, Jae-Yong (Division of International Maritime Transportation Science, Mokpo National Maritime University)
Publication Information
Journal of the Korean Society of Marine Environment & Safety / v.20, no.1, 2014 , pp. 33-41 More about this Journal
Abstract
Unlike the existing regression analysis, this study anticipated future marine traffic volume using time series analysis and artificial neural network model. Especially, it tried to anticipate future marine traffic volume by applying predictive value through time series analysis on artificial neural network model as an additional input variable. This study used monthly observed values of Incheon port from 1996 to 2013. In order for the verification of the forecasting of the model, value for 2013 is anticipated from the built model with observed values from 1996 to 2012 and a proper model is decided by comparing with the actual observed values. Marine traffic volume of Incheon port showed more traffic than average for May and November by 5.9 % and 4.5 % respectably, and January and August showed less traffic than average by 8.6 % and 4.7 % in 2015. Thus, it is found that Incheon port has difference in monthly traffic volume according to the season. This study can be utilized as a basis to reflect the characteristics of traffic according to the season when investigating marine traffic field observation.
Keywords
Autoregressive integrated moving average; Artificial neural network; Future marine traffic volume; Prediction; Season; Input variable; Incheon port;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
연도 인용수 순위
1 Quan, H. C., B. G. Lee, C. S. Lee and J. W. Ko(2011), The Landslide Probablility Analysis using Logistic Regression Analysis and Artficial Neural Network Methods in Jeju, Journal of the Kroean Society for Geo-Spatial Inforamtion System, Vol. 19, No. 3, pp. 33-40.
2 Kim, K. W., J. W. Jang and I. S. Cho(2011), A Study on Technique and Investigating Criterion for Improving Investigating Technique of Marine Traffic Volume, Proceedings of the Korean Society of Marine Environment Fall Conference, pp. 153-155.
3 Lee, D. W., H. M. Lee, J. W. Seo, S. H. Yoo and Y. H. Youn(2005), Storm Surge Prediction using Artificial Neural Network, Journal of Korean Meteorological Society, Vol. 41, No. 5, pp. 661-670.   과학기술학회마을
4 Park, S., K. J. Kim, J. S. Lee and S. R. Lee(2011), Red Tide Prediction using Neural Network and SVM, The Institute of Electronics Engineers of Korea-Signal Processing, Vol. 48, No. 5, pp. 39-45.   과학기술학회마을
5 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
6 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
7 SK Gas(2011), Maritime Traffic Safety Audit Report of SK 3 Wharf and SK Gas Wharf Expansion, Chapter 6, pp. 5-26.
8 Ulsan Port Authority(2013), Maritime Traffic Safety Audit Report of Construction at Namhwa Lighters Wharf in Ulsan Port, Chapter 4, pp. 18-22.
9 Yoo, S. R., Y. S. Park, J. S. Jeong, C. S. Kim and J. Y. Jeong(2013), A Forecast Method of Marine Traffic Volume through Time Series Analysis, Journal of the Korean Society of Marine Environment, Vol. 19, No. 6, pp. 612-620.   과학기술학회마을   DOI   ScienceOn
10 Akaike, H.(1978), A Bayesian Analysis of the minimum AIC Procedure, Annals of the Institute of Mathematical Statistics, pp. 9-14.
11 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.
12 Choi, S. H(2011), Neural Network Model for Prediction of Damage Cost from Storm and Flood, Journal of KIISE : Software and Applications, Vol. 38, No.3, pp. 115-123.   과학기술학회마을
13 Funahashi(1989), On the Approximate Realization of Continuous Mapping by Neural Networks, Neural Networks, Vol. 2, pp. 183-192.   DOI   ScienceOn
14 Gu, J. Y., S. J. Kim, E. K. Jang and S. W. Kim(2004), A Study on the Opimal width of the Main Span in the 2nd Bridge of Incheon, Journal of Korean Navigation and Port Research, Vol. 28, No. 10, pp. 933-940.   DOI
15 Hornik, K.(1989), Multilayer Feedforward Networks are Universal Approximators, Neural Networks, Vol. 2, pp. 359-366.   DOI   ScienceOn
16 Jang, S. C., S. M. Seok, J. S. Lee, S. W. Lee and B. H. Ahn(2005), Traffic-Flow Forecasting using ARIMA, Neural Network and Judgement Adjustment, Proceedings of The Korean Operations Research and Management Science Society Spring Conference, pp. 793-797.
17 Kang, M. S., Y. W. Kim and H. Jeong(2012), Predicition System of Floating Body Motion using Artficial Neural Networks, Joint Conference of the Korean Association of Ocean Science and Technology Societies, pp. 1041-1050.
18 Kang, S. W.(2012), A Study of Hull Form Design and Performance Predicition using Neural Networks, Proceedings of Korean Institute of Intelligent Systems Fall Conference, Vol. 22, No. 2, pp. 61-64.
19 Kim, J. G. and Y. D. Kim(2013), The Estimation of the Future Marine Traffic Volume at Expected Port which is an Additional Whart Construction, Proceedings of the Korean Society of Marine Environment Fall Conference, pp. 224-225.
20 Kim, J. H., S. G. Gug and M. C. Kim(2006), Estimation on the Future Traffic Volumne and Analysis on Crossing Situation Risk for Gamcheon Harbor, Journal of Korean Navigation and Port Research, Vol. 30, No. 8, pp. 617-622.   DOI