A Study of Development a Big Data-based CS Model for Maritime Traffic Assessment

• 발행기관: 한국항해항만학회
• 저자명: Eui-Jong Lee Hyun-suk Kim Seung-yeon Kim Young-Joong Ahn Yun-sok Lee
• 간행물 정보: 『한국항해항만학회지』제48권 제5호, 368~375쪽, 전체 8쪽
• 주제분류: 공학 > 해양공학
• 파일형태: PDF
• 발행일자: 2024.10.31

국문 초록

This research develops a big data-based CS model for maritime traffic assessment, motivated by global shipping growth, the impact of COVID-19, changes in consumer culture, and Industry 4.0 expansion in maritime sectors. Maritime traffic, crucial for global trade, demands effective management for safety and efficiency. This study aims to quantitatively and objectively evaluate maritime traffic smoothness by analyzing ship operation data. The CS model focuses on unique maritime characteristics, leveraging big data to enhance traffic management solutions and safety. The research methodology includes analyzing domestic and international trends and data to reflect maritime spatiality and continuity. The model's efficacy is tested through case studies on major port routes, comparing it with existing models to suggest improvements. This new approach provides a framework for optimizing maritime traffic routes and supports autonomous, unmanned, and smart ship operations, setting a new paradigm for maritime traffic management.

목차

1. Introduction

2. Maritime traffic flow model

3. Develop CS Model for maritime traffic flow assessment

4. Evaluation of with CS model

5. Conclusion

Acknowledgements

References

키워드

big data maritime traffic flow maritime traffic flow characteristics spatiality continuity CS model