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粤港澳大湾区港口群韧性能力评价与提升

刘鹏 黄希涞 潘智成 何清昊

集美大学学报(自然科学版)2026,Vol.31Issue(4):462-470,9.
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集美大学学报(自然科学版)2026,Vol.31Issue(4):462-470,9.DOI:10.19715/j.jmuzr.2026.04.07

粤港澳大湾区港口群韧性能力评价与提升

Resilience Evaluation and Enhancement of the Port Cluster in the Guangdong-Hong Kong-Macao Greater Bay Area

刘鹏 1黄希涞 1潘智成 2何清昊2

作者信息

  • 1. 广州航海学院未来交通学院,广东 广州 510725
  • 2. 广州航海学院未来交通学院,广东 广州 510725||广东工业大学土木与交通工程学院,广东 广州 510006
  • 折叠

摘要

Abstract

This study takes the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)port cluster as the research object,constructs an evaluation index system for port safety resilience in the GBA,and applies the en-tropy weight method to quantitatively assess the safety resilience of these ports.Resilience scores for each port are obtained,and key obstacle factors are identified through an obstacle degree model,based on which strate-gies for enhancing resilience are proposed.The research findings indicate that:1)Risk resistance capability plays a dominant role in the port safety resilience of the GBA,accounting for 50%of the total weight,while e-mergency response capability and recovery and reconstruction capability account for 26%and 24%,respective-ly.2)Guangzhou Port and Shenzhen Port demonstrate outstanding safety resilience,with scores of 0.82 and 0.75,significantly higher than those of other ports.3)In the core layer,the main obstacle factor for the GBA port cluster is risk resistance capability,while in the capability layer,the major obstacles are intelligent automa-tion level and innovation and upgrading capacity.

关键词

粤港澳大湾区/港口群/韧性能力/熵权法/障碍度模型

Key words

Guangdong-Hong Kong-Macao Greater Bay Area(GBA)/port cluster/resilience capability/en-tropy weight method/obstacle degree model

分类

交通工程

引用本文复制引用

刘鹏,黄希涞,潘智成,何清昊..粤港澳大湾区港口群韧性能力评价与提升[J].集美大学学报(自然科学版),2026,31(4):462-470,9.

基金项目

广州市教育局高校科研项目(Tertiary Education Scientific research project of Guangzhou Municipal Edu-cation Bureau,2024312403) (Tertiary Education Scientific research project of Guangzhou Municipal Edu-cation Bureau,2024312403)

集美大学学报(自然科学版)

1007-7405

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