A REVIEW OF MACHINE LEARNING TECHNIQUES FOR URBAN RESILIENCE RESEARCH: THE APPLICATION AND PROGRESS OF DIFFERENT MACHINE LEARNING TECHNIQUES IN ASSESSING AND ENHANCING URBAN RESILIENCE

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Chen, Yu;You, Wenxing;Ou, Lu;Tang, Hui

通讯作者：

Hui Tang

作者机构：

[Tang, Hui; Tang, H; Chen, Yu] Hunan City Univ, Coll Architecture & Urban Planning, Yiyang 413000, Peoples R China.

[You, Wenxing] Beijing Century Chief Int Architecture Design Co L, Beijing 110000, Peoples R China.

[Ou, Lu] Changsha Univ Sci & Technol, Sch Architecture, Changsha 410000, Hunan, Peoples R China.

[Tang, Hui; Tang, H; Chen, Yu] Hunan Prov Key Lab Urban Planning Informat Technol, Yiyang 413000, Peoples R China.

[Chen, Yu] Hunan Univ, Sch Architecture & Planning, Changsha 410000, Peoples R China.

通讯机构：

[Tang, H ] H

Hunan City Univ, Coll Architecture & Urban Planning, Yiyang 413000, Peoples R China.

Hunan Prov Key Lab Urban Planning Informat Technol, Yiyang 413000, Peoples R China.

语种：

英文

关键词：

machine learning;urban resilience;disaster management;data analytics;artificial intelligence

期刊：

Systems and Soft Computing

ISSN：

2772-9419

年：

2025

卷：

页码：

200269

DOI：

10.1016/j.sasc.2025.200269

基金类别：

Key Project of Education Department of Hunan Province [21A0506]; Teaching Reform Research Project of Hunan Province [HNJG-2022-0996]; Hunan Provincial Education Science 14th Five-Year Plan Project [ND247896]

机构署名：

本校为其他机构

院系归属：

建筑学院

摘要：

Urban resilience evaluates systems’ capacities to prepare for, adapt to, absorb, and recover from disruptions. Evaluation frameworks incorporate metrics like recovery speed, adaptive ability, and absorptive capacity. Assessing critical infrastructure interdependencies is challenging yet vital to limit failure propagation. While static assessments, multi-layer frameworks, and software like Hazus are used, limitations persist. Machine learning often focuses on infrastructure data for recovery monitoring. A common workflow entails acquiring and o...

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A REVIEW OF MACHINE LEARNING TECHNIQUES FOR URBAN RESILIENCE RESEARCH: THE APPLICATION AND PROGRESS OF DIFFERENT MACHINE LEARNING TECHNIQUES IN ASSESSING AND ENHANCING URBAN RESILIENCE

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