@inproceedings{f59b5b31f8904d1f9a2faa77bca15333,
title = "An attribute-based model to retrieve storm surge disaster cases",
abstract = "In China, storm surge disasters cause severe damages in coastal regions. One of the most critical 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 valuable information for the government to make real-time response plans.",
keywords = "Affected region prediction, Multiple attributes, Retrieval model, Storm surge disaster",
author = "Ke Wang and Genserik Reniers and Yongsheng Yang and Jian Li and Quanyi Huang",
year = "2021",
language = "English",
series = "Proceedings of the International ISCRAM Conference",
publisher = "Information Systems for Crisis Response and Management, ISCRAM",
pages = "567--580",
editor = "Anouck Adrot and Rob Grace and Kathleen Moore and Zobel, {Christopher W.}",
booktitle = "ISCRAM 2021 - Proceedings",
note = "18th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2021 ; Conference date: 23-05-2021 Through 26-05-2021",
}