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Author
Lida Huang
;
Guoray Cai
;
Hongyong Yuan
;
Jianguo Chen
;
Yan Wang
;
Feng Sun
Title
Modeling Threats of Mass Incidents Using Scenario-based Bayesian Network Reasoning
Type
Conference Article
Year
2018
Publication
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management
Abbreviated Journal
Iscram 2018
Volume
Issue
Pages
121-134
Keywords
Bayesian network, mass incidents, threat assessment, scenario analysis, interpretive structural modeling.
Abstract
Mass incidents represent a global problem, putting potential threats to public safety. Due to the complexity and uncertainties of mass incidents, law enforcement agencies lack analytical models and structured processes for anticipating potential threats. To address such challenge, this paper presents a threat analysis framework combining the scenario analysis method and Bayesian network (BN) reasoning. Based on a case library
Address
Corporate Author
Thesis
Publisher
Rochester Institute of Technology
Place of Publication
Rochester, NY (USA)
Editor
Kees Boersma; Brian Tomaszeski
Language
English
Summary Language
English
Original Title
Series Editor
Series Title
Abbreviated Series Title
Series Volume
Series Issue
Edition
ISSN
2411-3387
ISBN
978-0-692-12760-5
Medium
Track
Analytical Modeling and Simulation
Expedition
Conference
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
Notes
Approved
no
Call Number
Serial
2094
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