Holistic decision-making for optimal siting of urban earthquake emergency shelters: an integrated ontology and fuzzy-AHP approach

Li, Zimo, Khudhair, Ali ORCID: https://orcid.org/0000-0002-5062-7448 and Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133 2024. Holistic decision-making for optimal siting of urban earthquake emergency shelters: an integrated ontology and fuzzy-AHP approach. International Journal of Fuzzy Systems 10.1007/s40815-024-01889-8

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Abstract

Earthquakes are amongst the most destructive natural hazards, posing substantial risks to urban populations and infrastructure. As cities grow and modernise, identifying optimal locations for Urban Earthquake Emergency Shelters (UEES) becomes key for ensuring public safety. However, this process involves complex, multi-faceted criteria that must be carefully evaluated. This paper introduces a multi-criteria decision-making (MCDM) framework thatffiga integrates ontology with the fuzzy analytic hierarchy process (FAHP) to prioritise potential locations. A key contribution is the use of an ontology to model and interconnect the diverse criteria necessary for UEES site selection, providing a structured perspective that enhances both the theoretical understanding and practical decision-making in urban emergency management. The designed ontology structures and analyses the selection criteria, which are then processed using the FAHP to prioritise potential sites. This framework was validated through a case study in Beijing, where the Shijingshan and Haidian districts were identified as the most suitable locations due to high safety levels, economic benefits, and infrastructure interactions. The results also highlight key challenges in planning and construction across different sites. By combining ontology with FAHP, this framework optimises UEES location selection and supports the digital transformation of urban emergency management systems, offering a holistic, data-driven approach to disaster preparedness.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Engineering
Publisher:	Chinese Fuzzy Systems Association T
ISSN:	1562-2479
Date of First Compliant Deposit:	28 October 2024
Date of Acceptance:	30 September 2024
Last Modified:	03 Jan 2025 11:40
URI:	https://orca.cardiff.ac.uk/id/eprint/173464

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