4.8 Article

Why are Discrete Implications Necessary? An Analysis Through the Discretization Process

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Theory & Methods

T-norms and t-conorms on a family of lattices

C. Bejines

Summary: This paper provides a complete classification of all t-norms on a family of lattices in terms of t-norms on discrete chains, and computes the cardinal of some classes on discrete chains. The number of t-norms on the family of lattices is obtained. New results involving Archimedean and divisible t-norms are also presented, along with dual results for t-conorms.

FUZZY SETS AND SYSTEMS (2022)

Proceedings Paper Computer Science, Artificial Intelligence

A Novel Consensus Model For Group Decision-making Problems Based on Discrete Fuzzy Numbers

Ines Abdennaji et al.

Summary: The linguistic computational model based on discrete fuzzy numbers has attracted great interest among scholars due to its unique properties, however, there is a lack of research on group consensus using this model. This paper proposes a novel consensus model based on this framework, along with a new aggregation function and a semi-automatic algorithm for experts to interact and modify their opinions. This new method achieves significantly faster convergence rates in Group Decision Making compared to existing algorithms.

IEEE CIS INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS 2021 (FUZZ-IEEE) (2021)

Article Computer Science, Cybernetics

SMOOTH IMPLICATIONS ON A FINITE CHAIN

Yong Su

KYBERNETIKA (2019)

Proceedings Paper Telecommunications

Detection of infected wounds in abdominal surgery images using fuzzy logic and fuzzy sets

Manuel Gonzalez-Hidalgo et al.

2019 INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS (WIMOB) (2019)

Article Computer Science, Theory & Methods

Characterizations of idempotent discrete uninorms

Miguel Couceiro et al.

FUZZY SETS AND SYSTEMS (2018)

Article Computer Science, Artificial Intelligence

Characterization of Fuzzy Implication Functions With a Continuous Natural Negation Satisfying the Law of Importation With a Fixed t-Norm

Sebastia Massanet et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2017)

Article Computer Science, Theory & Methods

A characterization of discrete uninorms having smooth underlying operators

D. Ruiz-Aguilera et al.

FUZZY SETS AND SYSTEMS (2015)

Article Computer Science, Information Systems

A new linguistic computational model based on discrete fuzzy numbers for computing with words

Sebastia Massanet et al.

INFORMATION SCIENCES (2014)

Article Computer Science, Artificial Intelligence

A fuzzy mathematical morphology based on discrete t-norms: fundamentals and applications to image processing

Manuel Gonzalez-Hidalgo et al.

SOFT COMPUTING (2014)

Article Computer Science, Theory & Methods

Aggregation of subjective evaluations based on discrete fuzzy numbers

J. Vicente Riera et al.

FUZZY SETS AND SYSTEMS (2012)

Article Computer Science, Artificial Intelligence

On the law of importation (x ∧ y) → z ≡ (x → (y → z)) in fuzzy logic

Balasubramaniam Jayaram

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2008)

Article Computer Science, Artificial Intelligence

A survey on fuzzy implication functions

M. Mas et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2007)

Article Computer Science, Artificial Intelligence

Discrete copulas

A. Kolesarova et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2006)

Article Computer Science, Artificial Intelligence

Invariant fuzzy implications

J Drewniak

SOFT COMPUTING (2006)

Article Computer Science, Artificial Intelligence

On two types of discrete implications

M Mas et al.

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING (2005)

Article Computer Science, Theory & Methods

Automorphisms, negations and implication operators

H Bustince et al.

FUZZY SETS AND SYSTEMS (2003)

Article Statistics & Probability

Maximum and minimum extensions of finite subcopulas

H Carley

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS (2002)

Article Computer Science, Theory & Methods

Canonical representations of discrete fuzzy numbers

W Voxman

FUZZY SETS AND SYSTEMS (2001)