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Author (up) Stella Moehrle
Title Generic self-learning decision support system for large-scale disasters Type Conference Article
Year 2012 Publication ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2012
Volume Issue Pages
Keywords Artificial intelligence; Decision making; Decision support systems; Disaster prevention; Disasters; Information systems; Complex structure; Decision makers; Decision making process; Decision process; Disaster management; Emergency response; Large-scale disasters; Work in progress; Emergency services
Abstract Large-scale disasters, particularly failures of critical infrastructures, are exceptional situations which cannot be solved with standard countermeasures. The crises are complex and the decision makers face acute time pressure to respond to the disaster. IT based decision support systems provide potential solutions and assist the decision making process. Many decision support systems in emergency response and management concentrate on one kind of disaster. Moreover, complex structures are modeled and recommendations are made rule-based. This work in progress paper describes the first steps towards the development of a generic and self-learning decision support system. The methodology used is case-based reasoning. The paper concludes with a sample emergency decision process. © 2012 ISCRAM.
Address Institute for Nuclear and Energy Technologies, Karlsruhe Institute of Technology, Germany
Corporate Author Thesis
Publisher Simon Fraser University Place of Publication Vancouver, BC Editor L. Rothkrantz, J. Ristvej, Z.Franco
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780864913326 Medium
Track Track Decision Support Methods for Complex Crises Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 171
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