An integrated framework of early warning systems

Jie, Z; Jie, L; Guangquan, Z

An integrated framework of early warning systems

Jie, Z Jie, L

Guangquan, Z

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Publication Type:: Conference Proceeding
Citation:: World Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference, 2008, pp. 683 - 688
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Jie, Z	en_US
dc.contributor.author	Jie, L https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Guangquan, Z	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	World Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference, 2008, pp. 683 - 688	en_US
dc.identifier.isbn	981279946X	en_US
dc.identifier.isbn	9789812799463	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10858
dc.description.abstract	An early warning system (EWS) is critical to saving lives and mitigating loss from disasters. Literature addresses specific technical issues of EWSs in different hazard domains, however, only a few discussions on framework and standards. The paper proposes a set of practical designing standards and a comprehensive EWS integration framework. The framework takes considerations of human factors, lead-time and feedback issues, therefore more suitable for a wide range of applications in practice.	en_US
dc.relation.ispartof	World Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference	en_US
dc.title	An integrated framework of early warning systems	en_US
dc.type	Conference Proceeding
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	080105 Expert Systems	en_US
dc.location.activity	Madrid, Spain	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

An early warning system (EWS) is critical to saving lives and mitigating loss from disasters. Literature addresses specific technical issues of EWSs in different hazard domains, however, only a few discussions on framework and standards. The paper proposes a set of practical designing standards and a comprehensive EWS integration framework. The framework takes considerations of human factors, lead-time and feedback issues, therefore more suitable for a wide range of applications in practice.

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http://hdl.handle.net/10453/10858