Keywords
Fermatean fuzzy set, level set, fermatean subalgebra, Fermatean fuzzy subalgebra, Fermatean ideal, Fermatean homomorphism
Classical fuzzy sets have been generalized to better model uncertainty, leading to developments such as intuitionistic, Pythagorean, and Fermatean fuzzy sets. Fermatean fuzzy sets (ffss), characterized by the cube sum constraint on membership and non-membership degrees, provide a more flexible framework for handling complex uncertainty. BN-algebras are important algebraic structures with applications in logic and information theory.
This study integrates Fermatean fuzzy sets with BN-algebras by introducing the notions of Fermatean fuzzy subalgebras and Fermatean fuzzy ideals. Level cuts of Fermatean fuzzy sets are defined and analyzed, and algebraic techniques are employed to investigate their structural properties.
It is shown that Fermatean fuzzy level subalgebras and Fermatean fuzzy level ideals correspond to classical subalgebras and ideals of BN-algebras. Several characterizations and closure properties are established, supported by illustrative examples and rigorous proofs.
The results demonstrate that Fermatean fuzzy sets significantly enrich the theory of BN-algebras by accommodating higher degrees of uncertainty. This framework provides a solid theoretical foundation for further studies and potential applications in algebraic logic and uncertainty-based systems.
Fermatean fuzzy set, level set, fermatean subalgebra, Fermatean fuzzy subalgebra, Fermatean ideal, Fermatean homomorphism
Amendments from the Original Version!
We thank the reviewer for their valuable feedback. In response, we have made a few amendments from the original version of the manuscript. The conclusion has been updated to clarify that Fermatean BN-subalgebras and ideals can extend to other algebraic structures, including B-algebras, BCK/BCC-algebras, and BG-algebras. Reference [6] has been removed and citations adjusted, while the introduction now incorporates current bibliographic references. Essential definitions of BN-algebras and FFS remain in the Preliminaries section to maintain self-containment. Regarding redundancies, Definition 2.1 has been replaced with a fundamental definition from reference [3], Definition 2.11 has been removed, and related redundancies in Definition 2.4 have been corrected. We now explicitly acknowledge the limited literature on FFS in algebraic structures and suggest future work in algebraic logic, decision theory, and control theory. Finally, the revised manuscript includes a synthesized discussion with improved citations and a thorough grammar check to enhance clarity and coherence. We appreciate the reviewer's constructive input.
See the authors' detailed response to the review by Anjaneyulu Naik Kalavath
The concept of fuzzy sets (fs), introduced by zadeh,13 and has revolutionized the handling of uncertainty by allowing elements to have varying degrees of membership. this foundational idea was extended by atanassov3 with intuitionistic fuzzy sets (IFS), which added a degree of non-membership and yager12 further advanced this field with pythagorean fuzzy sets (PFS), where the square sum of membership and non-membership degrees is less than or equal to one. Adak, a.k., nilkaumal, and bb arman1 introduced Fermatean fuzzy semi-prime order semi groups, and the concept of Fermatean fuzzy set (FFS) was naturalized by senapati.t and yager,10 anas and et al.2 introduced the concepts of the direct product of sets that address the importance of Fermatean neutrosophic elements. y., komori7 introduced varieties of BCC-Algebra, the relation other algebraic structures, and j.neggers and H.S.kim8 introduced B-algebras, which are related to several generalizations of BCK-algebras, such as BCIci-algebras, BCH-algebras, BCC-algebras, BH-algebras, and9 D-algebras. In addition, Kim, C.B., and Km, hH.s discussed the concepts of BN-algebras with different structures, and grzegorz dymek and andrzej walendziak extend the concepts of ideals of BN-algebra to fuzzy ideals of BN-algebra4 with different properties. In this paper, we initiate the concept of a Fermatean fuzzy set on the ideals of BN-algebras and study its application. We state and prove some theorems discussed in the Fermatean fuzzy set on the ideals of BN-algebras and applications. We also extend the notions of an ideal and a normal ideal in a Fermatean fuzzy set on the ideals of BN-algebras.
3Let be a universe of study. An intuitionistic fuzzy sets (IFSs) in is an object
, where and satisfy the following criteria:
, for all in X, where and represents degree membership value and non-degree membership value of an element in
12The pythagorean fuzzy set defined on a nonempty set is of the form
for all
10Let be a universal set. A Fermatean fuzzy set (FF) in is
1Let be a universe of study. A Fermatean fuzzy set in is an object
12Algebra of type (2, 0) is called a BN-algebra if for all the following identities hold:
Let ℝ be the set of real numbers and let r = (ℝ, *, 0) be the algebra with the operation * defined by
6If BCI-algebra satisfies the condition it becomes a BCK-algebra. An algebra satisfies the condition:
7Algebra is said to be a BM-algebra if it satisfies the following axioms for all
11Algebra of type (2, 0) is called a BF-algebra if it satisfies the following axioms for all
Let F be a Fermatean fuzzy set (FFS) in . Then F is called a Fermatean fuzzy BN-subalgebra of x if the following conditions hold for all
where for all , andLet x = {0, 1, 2, 3, 4} be a set, and let * be defined by Table 1. The operation table defining the BN-algebra structure used in the following example is given in Table 1.
Then is a BN-algebra. Define by
Define
Let . Then is a subalgebra of the BN-algebra .
We have implies
Also
Hence and for all
Thus, is a Fermatean fuzzy subalgebra of
Let X be a BN-algebra and s be a subalgebra of x. Then
Let be a subalgebra of . Then imply . Since and 1, it follows that . Hence is nonempty.
Let . Then and . Since implies , it follows that . We get
Hence is a Fermatean fuzzy subalgebra of x. Moreover for all
Let be a BN-algebra and be the set of all Fermatean fuzzy subalgebras of . Then for we have:
are called level cuts of s. Here and are called the upper-level cut and lower-level cut of s respectively.
is a Fermatean subalgebra of x if and only if and for are subalgebra of .
Assume f is a Fermatean fuzzy subalgebra of x. We need to prove and are subalgebra of for
, implies and hence Therefore, is nonempty.
Let Then and . Put and . Now It follows that Hence which implies is a subalgebra of . Similar result holds for or .
Again let such that , for Imply that which implies is non-empty.
Let then and . Put now which imply we get therefore is a subalgebra of x a similar result holds for
Conversely, assume ) and are subalgebras of . We must prove is a Fermatean fuzzy subalgebra of .
Let and because and are subalgebras, we have and nonempty. Let and then and .
Suppose then put so that implies that which is a contradiction. Hence for the cases and with followed by a similar argument.
Again, let such that . Then put then we have which implies that which is not correct. Hence for all the cases and with follow by a similar argument thus is a Fermatean fuzzy subalgebra of
Let be a BN-algebra and let s be a subalgebra of . Then
Let x be a BN-algebra and let s be a subalgebra of x then
Is a Fermatean fuzzy subalgebra of with and for
Let S be a subalgebra of then imply since and , it follows that hence is nonempty.
Let then and and and since imply , it follows that we get
Hence F is a Fermatean fuzzy subalgebra of x moreover for all .
Let S be a subalgebra of then is a Fermatean level subset of s if and only if
Is a Fermatean fuzzy subalgebra of here for all .
Let be a level subset of S in .
Let X be a BN Algebra. Then Fermatean fuzzy ideal of x is defined by:
where and for allLet X = {0, a, b, c} and * be defined by Table 2.
If , then .
Let IFF be a Fermatean fuzzy ideal of a BN-algebra x then with the property
Let IFF be a Fermatean fuzzy ideal of a BN-algebra and be a degree membership function and for all
for all hence for all
Let be a BN-algebra and let be the set of Fermatean fuzzy ideals of then for for we have:
Let be a BN-algebra and if and only if the non-empty level subsets and are ideals of .
Let and with We need to prove and are ideals of
Let such that since we have implies .
Again, for x, such that and it follows that hence
Let and , imply and since it follows that
Again let such that then we have and since for all and we get it follows that hence therefore and are ideals of
Conversely, suppose and are ideals of x we must prove is Fermatean fuzzy ideal of for each is non-empty if such that then by assumption is an ideal of x hence so that which is a contradiction hence
Let , such that such that and β < δ_f(y) hence But this is impossible as is an ideal of to show is a Fermatean fuzzy ideal is simply taking the reverse of the proof done for . This completes the proof.
This paper has addressed a significant gap in the study of algebraic structures by exploring the application of Fermatean fuzzy sets to the ideals and sub-algebras of BN-algebras. The findings confirm that Fermatean fuzzy sets enrich the understanding of BN-algebras by accommodating imprecision more effectively, establishing new structural properties, and broadening the scope of algebraic studies under uncertainty. This makes them a valuable tool not only for theoretical mathematics but also for applications in computer science, decision-making systems, and information processing. For the future this work can be extended to other algebraic structures like BCK-algebra, BCCI-algebra, BCC-algebra, BG-algebra and related. It can also be applied to deal with more complex problems.
No datasets were generated or analyzed during this study. All results are derived analytically, and all supporting information is fully contained within the manuscript.
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Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Fuzzy Algebraic Structures, Hyper Algebraic Structures, Intuitionistic Fuzzy Algebraic Structures, Neutrosophic Fuzzy Algebraic Structures, Soft Sets, Rough Sets and Their Decision-Making Systems in Different algebraic structures.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?
No source data required
Are the conclusions drawn adequately supported by the results?
Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Fuzzy Metric Spaces, Fuzzy Normed Spaces, Fuzzy Inner Product Spaces.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?
No source data required
Are the conclusions drawn adequately supported by the results?
Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Fuzzy Algebraic Structures, Hyper Algebraic Structures, Intuitionistic Fuzzy Algebraic Structures, Neutrosophic Fuzzy Algebraic Structures, Soft Sets, Rough Sets and Their Decision-Making Systems in Different algebraic structures.
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