A neural network diagnosis model without disorder independence assumption

Xu, Y; Zhang, C

A neural network diagnosis model without disorder independence assumption

Xu, Y Zhang, C

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Publication Type:: Journal Article
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1998, 1531 pp. 341 - 352
Issue Date:: 1998-01-01

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Field	Value	Language
dc.contributor.author	Xu, Y	en_US
dc.contributor.author	Zhang, C https://orcid.org/0000-0001-5715-7154	en_US
dc.date.issued	1998-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1998, 1531 pp. 341 - 352	en_US
dc.identifier.isbn	9783540652717	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/13502
dc.description.abstract	© Springer-Verlag Berlin Heidelberg 1998. Generally, the disorders in a neural network diagnosis model are assumed independent each other. In this paper, we propose a neural network model for diagnostic problem solving where the disorder independence assumption is no longer necessary. Firstly, we characterize the diagnostic tasks and the causal network which is used to represent the diagnostic problem, then we describe the neural network diagnosis model, finally, some experiment results will be given.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/BFb0095282	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A neural network diagnosis model without disorder independence assumption	en_US
dc.type	Journal Article
utslib.citation.volume	1531	en_US
utslib.for	080101 Adaptive Agents and Intelligent Robotics	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	ISI:000084730100030	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (International)
pubs.organisational-group	/University of Technology Sydney/Strength - ACRI - Australia China Relations Institute
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	1531	en_US

Abstract:

© Springer-Verlag Berlin Heidelberg 1998. Generally, the disorders in a neural network diagnosis model are assumed independent each other. In this paper, we propose a neural network model for diagnostic problem solving where the disorder independence assumption is no longer necessary. Firstly, we characterize the diagnostic tasks and the causal network which is used to represent the diagnostic problem, then we describe the neural network diagnosis model, finally, some experiment results will be given.

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

http://hdl.handle.net/10453/13502