Ordinal Sums of Fuzzy Negations: Main Classes and Natural Negations

05/18/2019
by   Annaxsuel A. de Lima, et al.
0

In the context of fuzzy logic, ordinal sums provide a method for constructing new functions from existing functions, which can be triangular norms, triangular conorms, fuzzy negations, copulas, overlaps, uninorms, fuzzy implications, among others. As our main contribution, we establish conditions for the ordinal sum of a family of fuzzy negations to be a fuzzy negation of a specific class, such as strong, strict, continuous, invertible and frontier. Also, we relate the natural negation of the ordinal sum on families of t-norms, t-conorms and fuzzy implications with the ordinal sum of the natural negations of the respective families of t-norms, t- conorms and fuzzy implications. This motivated us to introduces a new kind of ordinal sum for families of fuzzy implications.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/29/2021

(S,N,T)-Implications

In this paper we introduce a new class of fuzzy implications called (S,N...
research
01/13/2017

Fuzzy Clustering Data Given in the Ordinal Scale

A fuzzy clustering algorithm for multidimensional data is proposed in th...
research
07/06/2022

Partial Residuated Implications Derived from Partial Triangular Norms and Partial Residuated Lattices

In this paper, we reveal some relations between fuzzy logic and quantum ...
research
12/19/2021

MISO hierarchical inference engine with fuzzy implication satisfying I(A(x, y), z) = I(x, I(y, z))

Fuzzy inference engine, as one of the most important components of fuzzy...
research
10/21/2010

New S-norm and T-norm Operators for Active Learning Method

Active Learning Method (ALM) is a soft computing method used for modelin...
research
10/25/2014

Parameterizing the semantics of fuzzy attribute implications by systems of isotone Galois connections

We study the semantics of fuzzy if-then rules called fuzzy attribute imp...
research
04/06/2021

An approach utilizing negation of extended-dimensional vector of disposing mass for ordinal evidences combination in a fuzzy environment

How to measure the degree of uncertainty of a given frame of discernment...

Please sign up or login with your details

Forgot password? Click here to reset