Statistical Foundations of Intelligent Technologies

Aboura, K

Statistical Foundations of Intelligent Technologies

Aboura, K

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Publisher:: University of Technology, Sydney
Publication Type:: Conference Proceeding
Citation:: Proceedings of The 8th International Conference on Intelligent Technologies (InTech07) : intelligent technologies in robotics and automation, 2007, pp. 1 - 7
Issue Date:: 2007-01

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Field	Value	Language
dc.contributor.author	Aboura, K	en_US
dc.contributor.editor	Ha, QP	en_US
dc.contributor.editor	Kwok, NM	en_US
dc.date	2007-12-12	en_US
dc.date.issued	2007-01	en_US
dc.identifier.citation	Proceedings of The 8th International Conference on Intelligent Technologies (InTech07) : intelligent technologies in robotics and automation, 2007, pp. 1 - 7	en_US
dc.identifier.isbn	978-1-86365-718-1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11871
dc.description.abstract	Intelligent Technologies problems have one common element; uncertainty. Randomness, natural or created, is an important part of the engineering problems in Intelligent Technologies. Modeling it properly and dealing with it in a coherent manner is essential to any solution. In this article, we address the issue of uncertainty in Intelligent Technologies through a classification problem. We look at the problems of pattern recognition and classification, an important area in automation, and use the example to highlight a simple but effective way to deal with uncertainty in complex environments	en_US
dc.publisher	University of Technology, Sydney	en_US
dc.relation.ispartof	Proceedings of The 8th International Conference on Intelligent Technologies (InTech07) : intelligent technologies in robotics and automation	en_US
dc.relation.ispartof	International Conference on Intelligent Technologies	en_US
dc.title	Statistical Foundations of Intelligent Technologies	en_US
dc.type	Conference Proceeding
utslib.location	Australia	en_US
utslib.location.activity	Sydney, Australia	en_US
utslib.for	090505 Infrastructure Engineering and Asset Management	en_US
utslib.for	010406 Stochastic Analysis and Modelling	en_US
utslib.for	010206 Operations Research	en_US
dc.location.activity	Sydney, Australia	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 Mechanical and Mechatronic Engineering
utslib.copyright.status	open_access
pubs.consider-herdc	false	en_US
pubs.place-of-publication	Australia	en_US
pubs.start-date	2007-12-12	en_US

Abstract:

Intelligent Technologies problems have one common element; uncertainty. Randomness, natural or created, is an important part of the engineering problems in Intelligent Technologies. Modeling it properly and dealing with it in a coherent manner is essential to any solution. In this article, we address the issue of uncertainty in Intelligent Technologies through a classification problem. We look at the problems of pattern recognition and classification, an important area in automation, and use the example to highlight a simple but effective way to deal with uncertainty in complex environments

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

http://hdl.handle.net/10453/11871