Development of Prediction Models for Container Stacking in Container Terminal

Lee, Do-Eun; Shin, Jae-Young

doi:2025.49.1.54

J Navig Port Res > Volume 49(1); 2025 > Article

Article

Journal of Navigation and Port Research 2025;49(1):54-59.
DOI: https://doi.org/10.5394/KINPR.2025.49.1.54 Published online February 28, 2025.

컨테이너 터미널의 컨테이너 장치 상태 예측 모형 개발

이도은¹, 신재영²

¹한국해양대학교 석사과정
²한국해양대학교 물류시스템학과 교수

Development of Prediction Models for Container Stacking in Container Terminal

Do-Eun Lee¹, Jae-Young Shin²

¹Student, Graduate School of National Korea Maritime University, Busan,606-791, Korea
²Professor, Departmen of Logistics Engineering, National Korea Maritime University, Busan 606-791, Korea

Correspondence: Jae-Young Shin, Tel: 051)410-4335,
Email: shinjy@kmou.ac.kr

Received: 9 January 2025 • Revised: 22 January 2025 • Accepted: 6 February 2025

Abstract

Maritime transportation accounts for the majority of global trade volume. Container terminals serve as crucial infrastructure playing a pivotal role in maritime logistics. The container yard within terminals is a key factor directly affecting operational efficiency. Its importance is increasingly emphasized due to recent growth in the shipping market, larger vessels, and increased cargo volume resulting from changes in international circumstances. This study presents a deep learning-based container status prediction model utilizing actual port operation data. It is a fundamental research study for establishing optimal yard planning to increase terminal yard operational efficiency. When actual measurements from port data were compared to predicted values through the prediction model, the proposed model was found to have a high prediction accuracy.

Key Words: container terminal, container yard, stacking status, prediction model, deep learning