A model for handling linguistic terms in the framework of lattice-valued logic LF(X)

Ma, J; Li, W; Xu, Y; Song, Z

A model for handling linguistic terms in the framework of lattice-valued logic LF(X)

Ma, J Li, W Xu, Y Song, Z

Permalink

Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Systems, Man and Cybernetics, 2004, pp. 1504 - 1509
Issue Date:: 2004-01

Closed Access

	Filename	Description	Size
	2006007241OK.pdf		425.73 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Ma, J	en_US
dc.contributor.author	Li, W	en_US
dc.contributor.author	Xu, Y	en_US
dc.contributor.author	Song, Z	en_US
dc.contributor.editor	NA	en_US
dc.date	2004-10-10	en_US
dc.date.issued	2004-01	en_US
dc.identifier.citation	IEEE International Conference on Systems, Man and Cybernetics, 2004, pp. 1504 - 1509	en_US
dc.identifier.isbn	0-7803-8566-7	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10823
dc.description.abstract	In this paper, focus on uncertainties, especially the incomparability, a framework of decision nza!&g with linguistic informataon is presented fmm the viewpoint of, lattice-valued first-order logic LF(X) based on lattice implication algebra. Concretely, the definitions of lattice implication algebra and proof in the lattice-valued first-order logic LF(X) are given firstly. Then the feature of each stage in a linguisticinformation- based decision making process is analyzed on the ground of a typical problem. Next, taking a linguistic term as a logical formula, a model for treating linguistic information is presented and compared with other methods on an example. Example has shown that the presented approach 1) doesnt require the using of fuzzy sets for interpretation of linguistic terms; 2) doesn% require the meanings of linguistic terms having predefined totally order, and 3) doesn$ require a linguistic term must take unique interpretation.	en_US
dc.publisher	IEEE	en_US
dc.relation.ispartof	IEEE International Conference on Systems, Man and Cybernetics	en_US
dc.relation.ispartof	IEEE Conference on Systems, Man and Cybernetics	en_US
dc.relation.isbasedon	10.1109/ICSMC.2004.1399844	en_US
dc.rights	© 2004 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.title	A model for handling linguistic terms in the framework of lattice-valued logic LF(X)	en_US
dc.type	Conference Proceeding
utslib.location	USA	en_US
utslib.location.activity	Hague, Netherlands	en_US
utslib.for	0806 Information Systems	en_US
dc.location.activity	Hague, Netherlands	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
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.place-of-publication	USA	en_US
pubs.start-date	2004-10-10	en_US

Abstract:

In this paper, focus on uncertainties, especially the incomparability, a framework of decision nza!&g with linguistic informataon is presented fmm the viewpoint of, lattice-valued first-order logic LF(X) based on lattice implication algebra. Concretely, the definitions of lattice implication algebra and proof in the lattice-valued first-order logic LF(X) are given firstly. Then the feature of each stage in a linguisticinformation- based decision making process is analyzed on the ground of a typical problem. Next, taking a linguistic term as a logical formula, a model for treating linguistic information is presented and compared with other methods on an example. Example has shown that the presented approach 1) doesnt require the using of fuzzy sets for interpretation of linguistic terms; 2) doesn% require the meanings of linguistic terms having predefined totally order, and 3) doesn$ require a linguistic term must take unique interpretation.

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

http://hdl.handle.net/10453/10823