Fuzzy network of reasoning by SVD and Morphotronic network

Resconi, G; Chaczko, Z

Fuzzy network of reasoning by SVD and Morphotronic network

Resconi, G Chaczko, Z

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Publication Type:: Conference Proceeding
Citation:: 2010 IEEE World Congress on Computational Intelligence, WCCI 2010, 2010
Issue Date:: 2010-11-25

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Field	Value	Language
dc.contributor.author	Resconi, G	en_US
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.date.issued	2010-11-25	en_US
dc.identifier.citation	2010 IEEE World Congress on Computational Intelligence, WCCI 2010, 2010	en_US
dc.identifier.isbn	9781424469208	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16208
dc.description.abstract	In the classical logic the inferential process is based on the modus ponens rule for which when the rule that connects the premise with the consequence is true and the premise is true, we know that the consequence is also true. Now, in the fuzzy inferential process the premise and the consequence are not logic propositions that assume the logic values true or false but are fuzzy sets that can assume values between zero and one. The classical logic rule is replaced with the fuzzy rule R. In this paper, we demonstrate that the fuzzy reasoning network is isomorphic to the Morphotronic network that includes the SVD technique. We also show that Morphotronic network is capable to simulate complex fuzzy reasoning or fuzzy inference in a completely new way. © 2010 IEEE.	en_US
dc.relation.ispartof	2010 IEEE World Congress on Computational Intelligence, WCCI 2010	en_US
dc.relation.isbasedon	10.1109/FUZZY.2010.5584018	en_US
dc.title	Fuzzy network of reasoning by SVD and Morphotronic network	en_US
dc.type	Conference Proceeding
utslib.for	080299 Computation Theory and Mathematics not elsewhere classified	en_US
utslib.for	080203 Computational Logic and Formal Languages	en_US
utslib.for	080201 Analysis of Algorithms and Complexity	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
dc.location.activity	Barcelona International Convention Centre, Barcelona, 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 Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

In the classical logic the inferential process is based on the modus ponens rule for which when the rule that connects the premise with the consequence is true and the premise is true, we know that the consequence is also true. Now, in the fuzzy inferential process the premise and the consequence are not logic propositions that assume the logic values true or false but are fuzzy sets that can assume values between zero and one. The classical logic rule is replaced with the fuzzy rule R. In this paper, we demonstrate that the fuzzy reasoning network is isomorphic to the Morphotronic network that includes the SVD technique. We also show that Morphotronic network is capable to simulate complex fuzzy reasoning or fuzzy inference in a completely new way. © 2010 IEEE.

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http://hdl.handle.net/10453/16208