International Journal of Fuzzy Logic and Intelligent Systems 2024; 24(3): 215-230
Published online September 25, 2024
https://doi.org/10.5391/IJFIS.2024.24.3.215
© The Korean Institute of Intelligent Systems
Sutapa Mahato1 and S. P. Tiwari2
1Centre for Data Science, ITER Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, India
2Department of Mathematics and Computing, Indian Institute of Technology (ISM), Dhanbad, India
Correspondence to :
Sutapa Mahato (sutapaiitdhanbad@gmail.com)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper establishes the relationship among L-fuzzy approximation spaces, L-fuzzy formal context analysis, and L-fuzzy Chu spaces, where L is a residuated lattice. Specifically, three types of L-fuzzy concept lattices are constructed based on generalized L-fuzzy rough approximation operators and linked to the classical L-fuzzy concept lattice, which is generated using Birkhoff operators. We further show that each L-fuzzy approximation space can be represented as an L-fuzzy Chu space, and this representation preserves products and co-products. Establishing these relationships not only provides a unified framework for different L-fuzzy concepts but also opens the way for further advancements in the theoretical foundation of fuzzy logic. This work bridges the gap between different mathematical approaches to fuzziness, offering new insights and tools in the field.
Keywords: L-fuzzy formal context, Concept lattice, L-fuzzy Chu space, L-fuzzy approximation spaces, Category, Product, Co-product
The authors declare no potential conflicts of interest relevant to this manuscript.
International Journal of Fuzzy Logic and Intelligent Systems 2024; 24(3): 215-230
Published online September 25, 2024 https://doi.org/10.5391/IJFIS.2024.24.3.215
Copyright © The Korean Institute of Intelligent Systems.
Sutapa Mahato1 and S. P. Tiwari2
1Centre for Data Science, ITER Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, India
2Department of Mathematics and Computing, Indian Institute of Technology (ISM), Dhanbad, India
Correspondence to:Sutapa Mahato (sutapaiitdhanbad@gmail.com)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper establishes the relationship among L-fuzzy approximation spaces, L-fuzzy formal context analysis, and L-fuzzy Chu spaces, where L is a residuated lattice. Specifically, three types of L-fuzzy concept lattices are constructed based on generalized L-fuzzy rough approximation operators and linked to the classical L-fuzzy concept lattice, which is generated using Birkhoff operators. We further show that each L-fuzzy approximation space can be represented as an L-fuzzy Chu space, and this representation preserves products and co-products. Establishing these relationships not only provides a unified framework for different L-fuzzy concepts but also opens the way for further advancements in the theoretical foundation of fuzzy logic. This work bridges the gap between different mathematical approaches to fuzziness, offering new insights and tools in the field.
Keywords: L-fuzzy formal context, Concept lattice, L-fuzzy Chu space, L-fuzzy approximation spaces, Category, Product, Co-product
Diagram for Theorem 3.1.
Diagram for Theorem 3.3.
Diagram for Theorem 3.3.
Diagram for Definition 5.4.
Diagram for Proposition 5.2.
Diagram for Theorem 5.1.
Diagram for Proposition 5.3.
Diagram for Theorem 5.2.
Sang Min Yun, Yeon Seok Eom, and Seok Jong Lee
International Journal of Fuzzy Logic and Intelligent Systems 2021; 21(4): 369-377 https://doi.org/10.5391/IJFIS.2021.21.4.369Won Keun Min
International Journal of Fuzzy Logic and Intelligent Systems 2019; 19(3): 158-162 https://doi.org/10.5391/IJFIS.2019.19.3.158Diagram for Theorem 3.1.
|@|~(^,^)~|@|Diagram for Theorem 3.3.
|@|~(^,^)~|@|Diagram for Theorem 3.3.
|@|~(^,^)~|@|Diagram for Definition 5.4.
|@|~(^,^)~|@|Diagram for Proposition 5.2.
|@|~(^,^)~|@|Diagram for Theorem 5.1.
|@|~(^,^)~|@|Diagram for Proposition 5.3.
|@|~(^,^)~|@|Diagram for Theorem 5.2.