Filter Theory in Pre-Ordered Residuated Systems Using Intuitionistic Fuzzy Points

Using the notion of intuitionistic fuzzy points, the concept of intuitionistic fuzzy filters and [Formula: see text]-intuitionistic fuzzy filters in pre-ordered residuated systems are introduced, and several related properties are investigated. Characterizations of intuitionistic fuzzy filters and [Formula: see text]-intuitionistic fuzzy filters are studied. By forming sub-structures called intuitionistic level set, intuitionistic [Formula: see text]-set, intuitionistic [Formula: see text]-set, and [Formula: see text]-set, the conditions under which they can be filters will be tracked.

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Publication Details

Journal
New Mathematics and Natural Computation
Published
2024-08-16
DOI
https://doi.org/10.1142/s1793005726500158
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Filter Theory in Pre-Ordered Residuated Systems Using Intuitionistic Fuzzy Points

Mehmet Ali̇ Öztürk, Damla Yılmaz, Young Bae Jun
New Mathematics and Natural Computation
Fuzzy Logic and Control Systems
article

Filter Theory in Pre-Ordered Residuated Systems Using Intuitionistic Fuzzy Points

Mehmet Ali̇ Öztürk, Damla Yılmaz, Young Bae Jun
article en

Abstract

Using the notion of intuitionistic fuzzy points, the concept of intuitionistic fuzzy filters and [Formula: see text]-intuitionistic fuzzy filters in pre-ordered residuated systems are introduced, and several related properties are investigated. Characterizations of intuitionistic fuzzy filters and [Formula: see text]-intuitionistic fuzzy filters are studied. By forming sub-structures called intuitionistic level set, intuitionistic [Formula: see text]-set, intuitionistic [Formula: see text]-set, and [Formula: see text]-set, the conditions under which they can be filters will be tracked.

New Mathematics and Natural ComputationVol. 22(01)
Gyeongsang National University (KR), Adıyaman University (TR), Erzurum Technical University (TR)
Openalex Percentile: Top 89%
Fuzzy Logic and Control Systems
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