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Author
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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