article

Fuzzy decision implications

Authors:

Kaishe QuAuthors Info & Claims

Knowledge-Based Systems, Volume 37

Pages 230 - 236

https://doi.org/10.1016/j.knosys.2012.08.004

Published: 01 January 2013 Publication History

Abstract

The aim of this paper is to provide the semantical and syntactical characteristics of fuzzy decision implications, an expression concerning two systems of fuzzy-sets. This Pavelka-style fuzzy logic starts from a fuzzy set of fuzzy decision implications and makes deductions from partially true decision implications. Following this idea, in semantical aspect, we present some basic results concerning completeness and more importantly, introduce the notion of ''unite closure'', which is in fact important not only in semantical aspect but also in syntactical aspect. Besides, we derive three deduction rules, namely (F-Transformation), (F-Add) and (F-Sh@6) for syntactical aspect of fuzzy decision implications, which are proved to be sound and complete with respect to semantical aspect. The result ensures that one can obtain a closed fuzzy set of fuzzy decision implications by the semantical way or by the syntactical way, i.e., by the three deduction rules.

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Cited By

Zhang SLi DZhai Y(2022)Incremental method of generating decision implication canonical basisSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-021-06452-326:3(1067-1083)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s00500-021-06452-3
Zeng WZhao YGu Y(2019)Similarity measure for vague sets based on implication functionsKnowledge-Based Systems10.1016/j.knosys.2015.11.01594:C(124-131)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1016/j.knosys.2015.11.015
Zhai YLi DQu K(2019)Decision implication canonical basisJournal of Computer and System Sciences10.1016/j.jcss.2014.06.00181:1(208-218)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1016/j.jcss.2014.06.001
Show More Cited By

Index Terms

Fuzzy decision implications
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic
2. Theory of computation
  1. Logic

Index terms have been assigned to the content through auto-classification.

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cover image Knowledge-Based Systems

Knowledge-Based Systems Volume 37, Issue

January, 2013

550 pages

ISSN:0950-7051

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2012.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 January 2013

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Cited By

Zhang SLi DZhai Y(2022)Incremental method of generating decision implication canonical basisSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-021-06452-326:3(1067-1083)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s00500-021-06452-3
Zeng WZhao YGu Y(2019)Similarity measure for vague sets based on implication functionsKnowledge-Based Systems10.1016/j.knosys.2015.11.01594:C(124-131)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1016/j.knosys.2015.11.015
Zhai YLi DQu K(2019)Decision implication canonical basisJournal of Computer and System Sciences10.1016/j.jcss.2014.06.00181:1(208-218)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1016/j.jcss.2014.06.001
Singh PAswani Kumar CGani A(2018)A comprehensive survey on formal concept analysis, its research trends and applicationsInternational Journal of Applied Mathematics and Computer Science10.1515/amcs-2016-003526:2(495-516)Online publication date: 15-Dec-2018
https://dl.acm.org/doi/10.1515/amcs-2016-0035
Xie JYang MLi JZheng Z(2018)Rule acquisition and optimal scale selection in multi-scale formal decision contexts and their applications to smart cityFuture Generation Computer Systems10.1016/j.future.2017.03.01183:C(564-581)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1016/j.future.2017.03.011
(2017)Comparison of reduction in formal decision contextsInternational Journal of Approximate Reasoning10.1016/j.ijar.2016.08.00780:C(100-122)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1016/j.ijar.2016.08.007
Kang XMiao D(2016)A study on information granularity in formal concept analysis based on concept-basesKnowledge-Based Systems10.1016/j.knosys.2016.05.005105:C(147-159)Online publication date: 1-Aug-2016
https://dl.acm.org/doi/10.1016/j.knosys.2016.05.005

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