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To Alert or Not to Alert? That Is the Question

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to_alert_or_not.pdf (341.3Kb)
Date
2019
Dewey
Recherche opérationnelle
Sujet
ICT and Artificial Intelligence for Crisis and Emergency Management; Collaboration Systems and Technologies; Crisis management; Decision tree; Decision support system; show 2 more
DOI
http://dx.doi.org/10.24251/HICSS.2019.080
Conference date
2019
Book title
52nd Hawaii International Conference on System Sciences, HICSS 2019
Author
Tung Bui
Publisher
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
ISBN
978-0-9981331-2-6
URI
https://basepub.dauphine.fr/handle/123456789/19627
Collections
  • LAMSADE : Publications
Metadata
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Author
Arru, Maude
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Negre, Elsa
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Rosenthal-Sabroux, Camille
Type
Communication / Conférence
Item number of pages
649-658
Abstract (EN)
Most of crises, environmental, humanitarian, economic or even social, occur after different presaging signals that permit to trigger warnings. These warnings can help to prevent damages and harm if they are issued timely and provide information that helps responders and population to adequately prepare for the disaster to come. Today, there are many systems based on Information and Communication Technologies that are designed to recognize foreboding signals of crises to limit their consequences. Warning system are part of them, they have proved to be effective, but as for all systems including human beings, a part of unpredictable remains. In this article, we provide a method of data analysis that allows decision makers in crisis cells to have answer elements to the question of alerting or not populations in a given geographical area. This method is based on a selection of factors that influence population behaviors, for which we establish a list of relevant indicators that can be informed in the preliminary phase of a crisis into warning systems. From these indicators, we propose a tool for decision support (based on a decision tree as a possible representation)

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