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Author (up) Ke Wang; Yongsheng Yang; Genserik Reniers; Jian Li; Quanyi Huang
Title An Attribute-based Model to Retrieve Storm Surge Disaster Cases Type Conference Article
Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021
Volume Issue Pages 567-580
Keywords Storm surge disaster, multiple attributes, retrieval model, affected region prediction
Abstract In China, storm surge disasters cause severe damages in coastal regions. One of the most important tasks is to predict affected regions and their relative damage levels to support decision-making. This study develops a two-stage retrieval model to search the most similar past disaster case to complete prediction. Based on spatial attributes of cases, the top-ranking past cases with a similar location to the target case are selected. Among these past cases, the most similar past case is selected by disaster attribute similarities. Three typical storm surge case studies have been used and implemented into this proposed model and the results show that all the most affected regions can be predicted. The proposed model simplifies the prediction process and updates results quickly. This study provides useful information for the government to make real-time response plans.
Address Tsinghua University; Tsinghua University; KU Leuven; Tsinghua University; Tsinghua University
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-61-5 ISBN Medium
Track Planning, Foresight and Risk Analysis Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management
Notes wangke16@mails.tsinghua.edu.cn Approved no
Call Number ISCRAM @ idladmin @ Serial 2356
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