A situation assessment approach using support vector machine as a learning tool

Lu, J; Liu, B; Zhang, G; Hao, Z; Xiao, Y

A situation assessment approach using support vector machine as a learning tool

Lu, J

Liu, B Zhang, G

Hao, Z Xiao, Y

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Publisher:: InderScience Publisher
Publication Type:: Journal Article
Citation:: International Journal of Nuclear Knowledge Management, 2008, 3 (1), pp. 82 - 97
Issue Date:: 2008-01

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Field	Value	Language
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Liu, B	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Hao, Z	en_US
dc.contributor.author	Xiao, Y	en_US
dc.date.issued	2008-01	en_US
dc.identifier.citation	International Journal of Nuclear Knowledge Management, 2008, 3 (1), pp. 82 - 97	en_US
dc.identifier.issn	1479-540X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9401
dc.description.abstract	In order to assess a situation and support decision makers' awareness for the situation, this study first proposes a situation assessment model with mathematical description. It then develops a Support Vector Machine based assessment approach, which has the ability to learn the rules from the previous assessment results and generate necessary warnings for a situation. Finally, a set of experiments is conducted to illustrate and validate the proposed approach.	en_US
dc.publisher	InderScience Publisher	en_US
dc.relation.ispartof	International Journal of Nuclear Knowledge Management	en_US
dc.title	A situation assessment approach using support vector machine as a learning tool	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	3	en_US
utslib.for	0915 Interdisciplinary Engineering	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.consider-herdc	true	en_US
pubs.issue	1	en_US
pubs.volume	3	en_US

Abstract:

In order to assess a situation and support decision makers' awareness for the situation, this study first proposes a situation assessment model with mathematical description. It then develops a Support Vector Machine based assessment approach, which has the ability to learn the rules from the previous assessment results and generate necessary warnings for a situation. Finally, a set of experiments is conducted to illustrate and validate the proposed approach.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/9401