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* Graduate school of Mokpo National Maritime University, Mokpo, 530-729, Korea** Division of Marine System Engineering, Korea Maritime and Ocean University, Busan, 606-791, Korea Division of International Maritime Transportation Science, Mokpo National Maritime University, Mokpo, 530-729, Korea :. ,. 1996 2013 .1996 20122013. 20155 11 5.9%, 4.5% , 1 88.6%, 4.7% ... : , , , , , , 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. Key Words : Autoregressive integrated moving average, Artificial neural network, Future marine traffic volume, Prediction, Season, Input variable, Incheon port*

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