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A Study on the Development of a Decision Support System Based on Physics and AI Models for Disaster Recovery Master Planning

Author(s): Giha Lee; Byungsik So; Dongkeun Lee; Eunyoung Jung; Kyoungdo Lee

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Keywords: ANP; BPA; DARP; Disaster Recovery Master Plan; Urban inundation

Abstract: Recent climate change has increased the frequency and intensity of extreme floods, leading to significant human and economic losses. To address these challenges, this study presents the DARP (Disaster Analysis & Recovery Planning) framework, an integrated, data-driven system that links urban inundation analysis with post-disaster recovery planning. The DARP process was applied to Phnom Penh, Cambodia, a flood-prone city, and integrates urban flood modeling with AI-based assessment methods to systematically analyze flood impacts and estimate economic losses. Based on these analyses, Business Priority Analysis (BPA) and the Analytic Network Process (ANP) were used to determine recovery priorities, which were then incorporated into a Disaster Recovery Master Plan (DRMP) that provides spatially explicit recovery strategies and directions for enhancing urban resilience.

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Year: 2026

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