항만 진출입 컨테이너 트럭의 터미널 도착량 예측에 관한 연구: 신선대, 감만 터미널을 대상으로

Abstract

Truck arrivals at a container terminal with a purpose of importing or exporting containers influence on a work plan in the terminal, which includes a management of traffics and safety in a seaport, plans of importing or exporting containers in the terminal, and assigning workers and equipments which are required for importing or exporting containers. Therefore truck arrivals are factors which influence on an efficient management plan for the container terminal. This paper develops a model which predicts truck arrival volume at Sinseondae and Gamman terminal, where are parts of Busan port in Korea, using a dataset of ship arrival and departure from these two terminals, a dataset of container import or export in the container terminal belongs to these terminals, and a machine learning method. And then the developed model is compared to a linear regression model with mean squared errors of the predicted values. Comparing to a linear regression model, the developed model shows a less mean squared error value. It is expected that the outputs from the model can be used for a management plan of the container terminal, and the developed model can be applied to other container terminals in Korea through an additional data collection.