Keywords
autometrized algebra, hesitant fuzzy subalgebra, hesitant fuzzy ideal, hesitant fuzzy congruence
This paper introduces the study of hesitant fuzzy subalgebras of autometrized algebras, obtains some of their properties, and gives some examples. Next, we introduce the concept of the hesitant fuzzy ideal and examine some of its properties. Finally, we introduce a hesitant fuzzy congruence on autometrized algebras and discuss some of its properties. We also introduce the characteristic equations and level subsets of hesitant fuzzy sets and relations on autometrized algebras.
autometrized algebra, hesitant fuzzy subalgebra, hesitant fuzzy ideal, hesitant fuzzy congruence
In this version, we add the following things according to the reviewers' comment and suggestions.
1. In the introduction section, We are incorporating a clear motivation, real-world relevance and a deeper comparison of hesitant fuzzy set with related works.
2. Examples are presented with sufficient explanation.
3. The definitions of hesitant fuzzy set operations and level sets are discussed.
4. We add a discussion section that explain the significance of hesitant fuzzy subalgebras, ideals, and congruences compared to traditional fuzzy sets or crisp sets. We also discuss practical situations or fields where these concepts are especially beneficial.
5. The future scope of the research is also discussed.
6. Recent reference materials are incorporated.
See the author's detailed response to the review by Sileshe Gone Korma
See the author's detailed response to the review by Ajoy Kanti Das
In his work,1 introduced the concept of autometrized algebras which includes Boolean algebras,2,3 Brouwerian algebras,4 Newman algebras,5 autometrized lattices,4 and commutative lattice-ordered groups (or l-groups).6 The study of ideals and congruences in autometrized algebras was conducted by Ref. 7. Further advancements in the theory of autometrized algebras were made by Refs. 7–22 developed the theory of subalgebras, ideals, and congruences of autometrized algebras. Moreover, Ref. 23 introduced the homomorphism, isomorphism, and correspondence theorems of autometrized algebra by using congruency.
The concept of fuzzy sets was introduced by Refs. 24–26 introduced the concept of hesitant fuzzy sets. Several researches were conducted on the generalizations of the notion of hesitant fuzzy sets and its applications such as Refs. 27–34. Recent studies have introduced various concepts, including to fuzzy soft group decision-making using weighted average ratings,35 parameterized intuitionistic fuzzy soft multiset and group decision-making,36 IFP-intuitionistic multi-fuzzy N-soft set and its induced IFP-hesitant N-soft set in decision-making,37 weighted hesitant bipolar-valued fuzzy soft set in decision-making38 and its corresponding IFP-hesitant N-soft set.39 These studies demonstrated that hesitant fuzzy sets are increasingly applied in multi-criteria decision-making, where decision-makers may be hesitant about different membership values for specific criteria. Additionally, they contributed to the creation of an efficient model for evaluating water quality.40 introduced fuzzy set theory applied on autometrized algebras.
Classical set theory and traditional fuzzy sets assign a single membership degree to each element. However, these approaches often fall short in addressing real-world problems that exhibit ambiguity, hesitation, or conflicting preferences. In such scenarios, classical set theory and even basic fuzzy set theory may not fully capture the complexities of decision-makers’ uncertainty. To address these limitations, the concept of hesitant fuzzy sets was introduced as a generalization of fuzzy sets. The key difference between fuzzy sets and hesitant fuzzy sets is that hesitant fuzzy set theory enhances fuzzy logic by allowing multiple membership degrees for an element within a set, thereby reflecting the hesitation among various possible values. Moreover, previous studies did not investigate hesitant fuzzy subalgebra, hesitant fuzzy ideal, and hesitant fuzzy congruence of autometrized algebra. Therefore, our motivation is to address these gaps. This paper introduces the concept of hesitant fuzzy subalgebras, hesitant fuzzy ideals, and hesitant fuzzy congruence relations on autometrized algebras.
The paper will be organized as follows: Section 2 will provide definitions and key terms. Section 3 will introduce the concept of hesitant fuzzy subalgebras of autometrized algebras. In Section 4, we will discuss hesitant fuzzy ideals of autometrized algebras. Section 5 will focus on hesitant fuzzy congruences on autometrized algebras. Finally, Section 6 will conclude the paper.
In this paper, Γ denotes an autometrized algebra (Γ, +, 0, ≼, ⋆).
This section examines essential concepts, definitions, and theorems important in other sections.
1 A system is called an autometrized algebra if
19 Let . Then is said to be a subalgebra of if;
7 An equivalence relation on is called a congruence relation if and only if
24 Let be a nonempty set, a fuzzy subset of is a mapping .
24 Let be a nonempty set and be a fuzzy subset of , for , the set is called a level subset of .
26 Let be a reference set. A hesitant fuzzy set on is a mapping , where means the power set of .
26 Let be a reference set. If , the characteristic hesitant fuzzy set on is a function of into defined as for all :
41 Let Then,
42 Let and let Then,
(i) the intersection of and , denoted by , is a hesitant fuzzy set on defined as for each , .
(ii) the intersection of , denoted by , is a hesitant fuzzy set on defined as for each , .
(iii) the union of and , denoted by , is a hesitant fuzzy set on defined as for each , .
(iv) the union of , denoted by , is a hesitant fuzzy set on defined as for each , .
26 Let be a hesitant fuzzy set on a nonempty set . Then, for all which is said to be the complement of on .
In this section, we will introduce the hesitant fuzzy subalgebras of autometrized algebras and explore several fundamental properties related to these subalgebras.
A hesitant fuzzy subset of is called a hesitant fuzzy subalgebra of if for all ;
Let with and elements are incomparable. Define and by the following tables.
Then, is an autometrized algebra. Define a hesitant fuzzy subset of by: and . Now, check the two closure properties,
Therefore, is hesitant fuzzy subalgebra of .
If is a hesitant fuzzy subalgebra of , then for ; .
Assume that is a hesitant fuzzy subalgebra of . Then, . This implies that . Therefore, .
Let is a nonempty subset of . if and only if for all .
Assume that . So, . Therefore, for all .
Conversely, assume that for all . Since is nonempty subset of , we have for . Therefore, . As a result, . Hence, .
A nonempty subset of is a subalgebra of if and only if the characteristic hesitant fuzzy set is a hesitant fuzzy subalgebra of .
Assume that is subalgebra of . Let .
Conversely, assume that is a hesitant fuzzy subalgebra of Γ. To show that is a subalgebra of .
(i) To show that . Since for all ; by theorem (3.4), .
(ii) Let . Then, and . Since is a hesitant fuzzy subalgebra of ; . So, . Hence, .
(iii) Let . Then, and . Since is a hesitant fuzzy subalgebra of ; . So, . Hence, . Hence is a subalgebra of .
Let be a hesitant fuzzy set of . For all , define the level subsets of as , , , and .
Let be a hesitant fuzzy set of . Then is a hesitant fuzzy subalgebra of if and only if for all , is a subalgebra of .
Assume that is a hesitant fuzzy subalgebra of . To show that is a subalgebra of . Let be such that .
(i) Let . Then, . Since is a hesitant fuzzy subalgebra of , implies that . Therefore, .
(ii) Let . Then, and . Since is a hesitant fuzzy subalgebra of ; . This implies that .
(iii) Let . Then, and . Since is a hesitant fuzzy subalgebra of ; . This implies that . Hence, is a subalgebra of .
Conversely, assume that is a subalgebra of . To show that is a hesitant fuzzy subalgebra of .
(i) Let . Take . Therefore, and . As a result, . Since is a subalgebra of ; . Hence, .
(ii) Let . Take . Therefore, and . As a result, . Since is a subalgebra of ; . Hence, .
Hence, is a hesitant fuzzy subalgebra of .
Let be a hesitant fuzzy set of . If is a chain and for all , is a subalgebra of , then is a hesitant fuzzy subalgebra of .
Assume that is a chain and for all , a nonempty subset is a subalgebra of . To show that is a hesitant fuzzy subalgebra of .
(i) Let . To show that . Suppose that . Since is a chain; implies that . Take . Therefore, and . As a result, . Since is a subalgebra of ; . So, . This is a contradiction. Thus, for all .
(ii) Let . To show that . Suppose that . Since is a chain; implies that . Take . Therefore, and . As a result, . Since is a subalgebra of ; . So, . This is a contradiction. Thus, for all .
Hence, is a hesitant fuzzy subalgebra of .
Let be a hesitant fuzzy set of . Then is a hesitant fuzzy subalgebra of if and only if for all , is a subalgebra of .
Assume that is a hesitant fuzzy subalgebra of . To show that is a subalgebra of . Let be such that .
(i) Let . Then, . Since is a hesitant fuzzy subalgebra of , implies that . Clearly, . Therefore, . Therefore, .
(ii) Let . Then, and . Since is a hesitant fuzzy subalgebra of ; . So, . Therefore, . Hence, .
(iii) Let . Then, and . Since is a hesitant fuzzy subalgebra of ; . So, . Therefore, . Hence, . Therefore, is a subalgebra of .
Conversely, assume that is a subalgebra of . To show that is a hesitant fuzzy subalgebra of .
(i) Let . Take . Therefore, and . As a result, . Since is a subalgebra of ; . Clearly, . As a result, . Therefore, .
(ii) Let . Take . Therefore, and . As a result, . Since is a subalgebra of ; . Clearly, . As a result, . Therefore, .
Hence, is a hesitant fuzzy subalgebra of .
Let be a hesitant fuzzy set of . If is a chain and for all , is a subalgebra of , then is a hesitant fuzzy subalgebra of .
Assume that is a chain and for all , a nonempty subset is a subalgebra of . To show that is a hesitant fuzzy subalgebra of .
(i) Let . To show that . Suppose that . Since is a chain; implies that . Clearly, . So, . Take . Therefore, and . As a result, . Since is a subalgebra of ; . So, . This is a contradiction. Thus, for all .
(ii) Let . To show that . Suppose that . Since is a chain; implies that . Clearly, . So, . Take . Therefore, and . As a result, . Since is a subalgebra of ; . So, . This is a contradiction. Thus, for all . Hence, is a hesitant fuzzy subalgebra of .
This section presents the concept of hesitant fuzzy ideals in autometrized algebras and explores several fundamental properties related to these ideals.
A hesitant fuzzy subset of is called a hesitant fuzzy ideal of if for all ;
Let with and elements are incomparable. Define and by the following tables.
Then, is an autometrized algebra. Define a hesitant fuzzy subset of by:
Now, check the two closure properties,
Therefore, is a hesitant fuzzy ideal of .
If is a hesitant fuzzy ideal of , then for ; .
Assume that is a hesitant fuzzy ideal of . Since ; implies that that .
Let be a normal autometrized algebra. If is a hesitant fuzzy ideal of , then for ; .
Assume that is a hesitant fuzzy ideal of . Since is normal; implies that . This implies that and ; implies that and . Therefore, .
Let be a normal autometrized algebra. Every hesitant fuzzy ideal of is a hesitant fuzzy subalgebra of .
Assume that is a hesitant fuzzy ideal of . Let .
Therefore, . Hence, is a hesitant fuzzy subalgebra of .
A nonempty subset of is an ideal of if and only if the characteristic hesitant fuzzy set is a hesitant fuzzy ideal of .
Assume that is an ideal of . Let .
Hence, is a hesitant fuzzy ideal of .
Conversely, assume that is a hesitant fuzzy ideal of . To show that is an ideal of .
Let be a hesitant fuzzy set of . Then is a hesitant fuzzy ideal of if and only if for all , a nonempty subset is an ideal of .
Assume that is a hesitant fuzzy ideal of . To show that is an ideal of . Let be such that .
(i) Let . Then, and . Since is a hesitant fuzzy ideal of ; . This implies that .
(ii) Let . Suppose . Let . Clearly, . To show that . Since is a hesitant fuzzy ideal of , . Therefore, . Thus, . Hence, is an ideal of .
Conversely, assume that is an ideal of . To show that is a hesitant fuzzy ideal of .
(i) Let . Take . Therefore, and . As a result, . Since is an ideal of ; . Hence, .
(ii) Let . Suppose . Take . So, . Since is an ideal; . As a result, .
Hence, is a hesitant fuzzy ideal of .
Let be a hesitant fuzzy set of . If is a chain and for all , a nonempty subset is an ideal of , then is a hesitant fuzzy ideal of .
Assume that is a chain and for all , a nonempty subset is an ideal of . To show that is a hesitant fuzzy ideal of .
(i) Let . To show that . Suppose that . Since is a chain; implies that . Then, . Take . Therefore, and . As a result, . Since is an ideal of ; . So, . This is a contradiction. Thus, for all .
(ii) Let . Suppose . To show that . Suppose that . Since is a chain; implies that . Then, . Take . Therefore, . As a result, . Since is an ideal of ; . So, . This is a contradiction. Therefore, for all .
Hence, is a hesitant fuzzy ideal of .
Let be a hesitant fuzzy set of . Then is a hesitant fuzzy ideal of if and only if for all , a nonempty subset is an ideal of .
Assume that is a hesitant fuzzy ideal of . To show that is an ideal of . Let be such that .
(i) Let . Then, . Since is a hesitant fuzzy ideal of , implies that . Clearly, . Therefore, . Therefore, .
(ii) Let . Then, and . Since is a hesitant fuzzy ideal of ; . So, . Therefore, . Hence, .
(iii) Let . Suppose . Let . Clearly, . To show that . Since is a hesitant fuzzy ideal of , . So, . Therefore, . Thus, . Hence, is an ideal of .
Conversely, assume that is an ideal of . To show that is a hesitant fuzzy ideal of .
Let be a hesitant fuzzy set of . If is a chain and for all , a nonempty subset is an ideal of , then is a hesitant fuzzy ideal of .
Assume that is a chain and for all , a nonempty subset is an ideal of . To show that is a hesitant fuzzy ideal of .
(i) Let . To show that . Suppose that . Since is a chain; implies that . Clearly, . So, . Take . Therefore, and . As a result, . Since is an ideal of ; . So, . This is a contradiction. Thus, for all .
(ii) Let . Suppose . To show that . Suppose that . Since is a chain; implies that . Then, . Clearly, . Take . Therefore, . As a result, . Since is an ideal of ; . So, . This is a contradiction. Therefore, for all . Hence, is a hesitant fuzzy ideal of .
In this section, we introduce the hesitant fuzzy congruence relation of autometrized algebras and examine some related properties.
A hesitant fuzzy relation on is a mapping , where means the power set of .
Let be a hesitant fuzzy relation on . Then, for all which is said to be the complement of on .
If is a hesitant fuzzy equivalent relation on , then
A hesitant fuzzy equivalence relation on is called a hesitant fuzzy congruence relation on if
In Example 3.2, becomes an autometrized algebra. Define a hesitant fuzzy relation on by: and .
Now, check the three closure properties,
Therefore, is a hesitant fuzzy congruence relation on .
If is a relation on , then characteristic hesitant fuzzy relation on is a function of into defined as for all :
A nonempty equivalent relation on is a congruence relation on if and only if the characteristic hesitant fuzzy equivalent relation is a hesitant fuzzy congruence relation on .
Assume that is a congruence relation on . To show that is a hesitant fuzzy congruence relation on . Let .
(i) To show that . Here we will consider two cases.
(ii) To show that . Here we will consider two cases.
(iii) Let and suppose that . To show that . Here we will consider two cases.
Conversely, assume that is a hesitant fuzzy congruence relation on . To show that is a congruence relation on .
(i) Let . Then, and . Since is a hesitant fuzzy congruence relation on ; . So, . Hence, .
(ii) Let . Then, and . Since is a hesitant fuzzy congruence relation on ; . So, . Hence, .
(iii) Let and . Clearly, . Since is a hesitant fuzzy congruence relation on ; then . Therefore, . Hence, . Hence, is a congruence relation on .
Let be a hesitant fuzzy relation on . For all , the sets , , , and are called level subset of .
Let be a hesitant fuzzy relation on . is a hesitant fuzzy congruence relation on if and only if for all , is either empty or a congruence relation on .
Assume that is a hesitant fuzzy congruence relation on .
(i) Since is a nonempty; let . So, . But . So, . Therefore, .
(ii) Let . So, . Clearly, . So, . Therefore, .
(iii) Let . Then, and . Clearly, . Since is a hesitant fuzzy congruence; . Therefore, . Therefore, is an equivalence relation.
(a) Let . So, and . Since is a hesitant fuzzy congruence relation on ; . Therefore, .
(b) Let . So, and . Since is a hesitant fuzzy congruence relation on ; . Therefore, .
(c) Let and . Clearly, . Since is a hesitant fuzzy congruence relation on ; then . Therefore, . Hence, is a congruence relation on .
Conversely, is a congruence relation on . To show that is a hesitant fuzzy congruence relation on .
(i) We know that for any , . Take . So, . Since is a congruence relation; . Then, . Therefore, .
(ii) Let . Take . So, . Since is a congruence; . So, . Clearly, . Again, take . So, . Since is a congruence; . So, . Clearly, . Consequently, .
(iii) Let . Take . Clearly, and . This implies that . Since is a congruence relation; . Therefore, . Thus, . Therefore, is a hesitant equivalence relation.
(a) Let . Take . Therefore, and . Since is a congruence relation on ; . As a result, .
(b) Let . Take . Therefore, and . Since is a congruence relation on ; . As a result, .
(c) Let and suppose that . Take . Therefore, . Since is a congruence relation on ; . Therefore, . Hence, is a hesitant fuzzy congruence relation on .
Let be a hesitant fuzzy equivalent relation on . If is a chain and for all , a nonempty subset is a congruence relation on , then is a hesitant fuzzy congruence relation on .
Assume that is a chain and for all , a nonempty subset is a congruence relation on . To show that is a hesitant fuzzy congruence relation on .
(i) Let . To show that . Suppose that . Since is a chain; implies that . Then, . Take . Therefore, and . As a result, . Since is a congruence relation on ; . So, . This is a contradiction. Thus, for all .
(ii) Let . To show that . Suppose that . Since is a chain; implies that . Then, . Take . Therefore, and . As a result, . Since is a congruence relation on ; . So, . This is a contradiction. Thus, for all .
(iii) Let and suppose that . To show that . Suppose that Suppose that . Since is a chain; implies that . Take . Therefore, . Since is a congruence relation on relation on ; . Therefore, is contradiction. Therefore, . Hence, is a hesitant fuzzy congruence relation on .
Let be a hesitant fuzzy equivalent relation on . Then is a hesitant fuzzy congruence relation on if and only if for all , is either empty or congruence relation on .
Assume that is a hesitant fuzzy congruence relation on . To show that is a congruence relation on . Let be such that .
(i) Since is a nonempty; let . So, . Since is a hesitant fuzzy congruence relation on ; . Then, . As a result, . Therefore, .
(ii) Let . So, . Since is a hesitant fuzzy congruence relation on ; . Clearly, . So, . Therefore, .
(iii) Let . Then, and . Since is a hesitant fuzzy congruence relation on ; . Then, . Consequently, . Therefore, . Therefore, is an equivalence relation.
(a) Let . Then, and . Since is a hesitant fuzzy congruence relation on ; . So, . Therefore, . Hence, .
(b) Let . Then, and . Since is a hesitant fuzzy congruence relation on ; . So, . Therefore, . Hence, .
(c) Let and . Clearly, . To show that . Since is a hesitant fuzzy congruence relation on , . So, . Therefore, . Thus, . Hence, is congruence relation on .
Conversely, assume that is congruence relation on . To show that is a hesitant fuzzy congruence relation on .
(i) We know that for any , . Take . So, . Since is a congruence relation; . Then, . So, . Clearly, . Therefore, .
(ii) Let . Take . So, . Since is a congruence; . So, . Therefore, . Clearly, . Therefore, . Again, take . So, . Since is a congruence; . So, . Clearly, . Clearly, . Therefore, . Hence, .
(iii) Let . Take . Clearly, and . This implies that . Since is a congruence relation; . Therefore, . Clearly, . Now, consider . As a result, . Therefore, is a hesitant equivalence relation.
(a) Let . Take . Therefore, and . As a result, . Since is a congruence relation on ; . Clearly, . As a result, . Therefore, .
(b) Let . Take . Therefore, and . As a result, . Since is a congruence relation on ; . Clearly, . As a result, . Therefore, .
(c) Let and suppose that . Take . So, . Since is a congruence relation on ; . As a result, . Clearly, . Therefore, . Hence, is a hesitant fuzzy congruence relation on .
Let be a hesitant fuzzy equivalent relation on . If is a chain and for all , a nonempty subset is a congruence relation on , then is a hesitant fuzzy congruence relation on .
Assume that is a chain and for all , a nonempty subset is a congruence relation on . To show that is a hesitant fuzzy congruence relation on .
(i) Let . To show that . Suppose that . Since is a chain; implies that . Then, . Clearly, . So, . Take . Therefore, and . As a result, . Since is a congruence relation on ; . So, . This is a contradiction. Thus, .
(ii) Let . To show that . Suppose that . Since is a chain; implies that . Then, . Clearly, . So, . Take . Therefore, and . As a result, . Since is a congruence relation on ; . So, . This is a contradiction. Thus, .
(iii) Let and suppose that . To show that . Suppose that . Since is a chain; implies that . Then, . Clearly, . Take . Therefore, . As a result, . Since is a congruence relation on ; . So, . This is a contradiction. Therefore, . Hence, is a hesitant fuzzy congruence relation on .
In this section, we explain the significance of hesitant fuzzy subalgebras, ideals, and congruences compared to traditional fuzzy sets or crisp sets. We also discuss practical situations or fields where these concepts are especially beneficial.
Hesitant fuzzy sets are valuable in any domain where there is uncertainty or hesitation in assigning precise membership values. Unlike traditional fuzzy sets and crisp sets, hesitant fuzzy sets provide a flexible framework for managing ambiguity in decision-making, pattern recognition, image processing, medical diagnosis, data mining, risk analysis, artificial intelligence, and control systems and robotics, among other applications.35–39,41 Their ability to represent multiple membership values makes them particularly well-suited for complex, real-world problems where traditional fuzzy sets or crisp values may fall short.
Hesitant fuzzy subalgebras are useful for modeling systems where uncertainty affects internal consistency. For example, in cognitive processes or machine learning models, an object may partially belong to multiple substructures. Additionally, hesitant fuzzy ideals allow us to identify desirable or stable subsets within a system where boundaries are not sharply defined, which is especially useful in optimization and control. Finally, hesitant fuzzy congruences generalize equivalence relations for systems with vague class memberships, making them essential for tasks such as pattern recognition and fault-tolerant classification.
This paper introduced the study of hesitant fuzzy subalgebras of autometrized algebras. Also, we proved that a nonempty subset of an autometrized algebra is a subalgebra of if and only if the characteristic hesitant fuzzy set is a hesitant fuzzy subalgebra of . Further, we introduced the concept of the hesitant fuzzy ideal and examined some of its properties. We showed that hesitant fuzzy set on an autometrized algebra is a hesitant fuzzy ideal of if and only if for all , a nonempty subset is an ideal of . Finally, we introduced a hesitant fuzzy congruence on autometrized algebras and discussed some of its properties. In particular, we explored a hesitant fuzzy equivalent relation on an autometrized algebra is a hesitant fuzzy congruence relation on if and only if for all , is either empty or congruence relation on .
In a future study, we will extend our research to interval-valued fuzzy subalgebras, ideals, and congruences, and investigate their algebraic characteristics. Interval-valued fuzzy sets enhance our ability to model and manage uncertainty and imprecision in complex systems. By incorporating a range of membership degrees, this approach enriches traditional fuzzy set theory, providing a more robust and flexible framework for decision-making in uncertain situations. This is especially relevant in fields such as risk assessment, medical diagnosis, environmental modeling, and engineering design, where precise data is often unavailable or incomplete. Despite theoretical richness, hesitant fuzzy sets are not widely adopted in industrial or real-world systems due to their complexity and the availability of simpler alternatives such as interval-valued fuzzy sets.
All authors made equal contributions to this manuscript and have approved the final version.
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Competing Interests: No competing interests were disclosed.
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?
Not applicable
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?
Partly
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?
Not applicable
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
References
1. Weighted hesitant bipolar-valued fuzzy soft set in decision-making. Songklanakarin Journal of Science and Technology, 45(6): 681-690 https://sjst.psu.ac.th/journal/45-6/10.pdf.Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Fuzzy set theory and its applications, Soft set and Decision-making, Soft Computing, Sequence space, Topology
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?
Not applicable
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: Algebra, lattice theory, universal algebra, fuzzy algebra
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