Abstract
The notions of the neutrosophic hesitant fuzzy subalgebra and neutrosophic hesitant fuzzy filter in pseudo-BCI algebras are introduced, and some properties and equivalent conditions are investigated. The relationships between neutrosophic hesitant fuzzy subalgebras (filters) and hesitant fuzzy subalgebras (filters) is discussed. Five kinds of special sets are constructed by a neutrosophic hesitant fuzzy set, and the conditions for the two kinds of sets to be filters are given. Moreover, the conditions for two kinds of special neutrosophic hesitant fuzzy sets to be neutrosophic hesitant fuzzy filters are proved.
1. Introduction
G. Georgescu and A. Iogulescu presented pseudo-BCKalgebras, which was an extension of the famous BCK algebra theory. In [1], the notion of the pseudo-BCI algebra was introduced by W.A. Dudek and Y.B. Jun. They investigated some properties of pseudo-BCI algebras. In [2], Y.B. Jun et al. presented the concept of the pseudo-BCI ideal in pseudo-BCI algebras and researched its characterizations. Then, some classes of pseudo-BCI algebras and pseudo-ideals (filters) were studied; see [3,4,5,6,7,8,9,10,11,12,13,14].
In 1965, Zadeh introduced fuzzy set theory [15]. In the study of modern fuzzy logic theory, algebraic systems played an important role, such as [16,17,18,19,20,21,22]. In 2010, Torra introduced hesitant fuzzy set theory [23]. The hesitant fuzzy set was a useful tool to express peoples’ hesitancy in real life, and uncertainty problems were resolved. Furthermore, hesitant fuzzy sets have been applied to decision making and algebraic systems [24,25,26,27,28,29,30,31]. As a generalization of fuzzy set theory, Smarandache introduced neutrosophic set theory [32]; the neutrosophic set theory is a useful tool to deal with indeterminate and inconsistent decision information [33,34]. The neutrosophic set includes the truth membership, indeterminacy membership and falsity membership. Then, Wang et al. [35,36] introduced the interval neutrosophic set and single-valued neutrosophic set. Ye [37] introduced the single-valued neutrosophic hesitant fuzzy set as an extension of the single-valued neutrosophic set and hesitant fuzzy set. Recently, the neutrosophic triplet structures were introduced and researched [38,39,40].
In this paper, some preliminary concepts in pseudo-BCI algebras, hesitant fuzzy set theory and neutrosophic set theory are briefly reviewed in Section 2. In Section 3, the notion of neutrosophic hesitant fuzzy subalgebras in pseudo-BCI algebras is introduced. The relationships between neutrosophic hesitant fuzzy subalgebras and hesitant fuzzy subalgebras are investigated. Five kinds of special sets are constructed. Some properties are studied. Third, the two kinds of sets to be filters are given. In Section 4, the concept of neutrosophic hesitant fuzzy filters in pseudo-BCI algebras is proposed. The equivalent conditions of the neutrosophic hesitant fuzzy filters in the construction of hesitant fuzzy filters are given. The conditions for two kinds of special neutrosophic hesitant fuzzy sets to be neutrosophic hesitant fuzzy filters are given.
2. Preliminaries
Let us review some fundamental notions of pseudo-BCI algebra and interval-valued hesitant fuzzy filter in this section.
Definition 1.
([13]) A pseudo-BCI algebra is a structure (X; →, ↪, 1), where “→” and “↪” are binary operations on X and “1” is an element of X, verifying the axioms: ,
- (1)
- , ;
- (2)
- , ;
- (3)
- ;
- (4)
- ;
- (5)
- .
If (X; →, ↪, 1) is a pseudo-BCI algebra satisfying , , then (X; →, 1) is a BCI algebra. If (X; →, ↪, 1) is a pseudo-BCI algebra satisfying , , then (X; →, ↪, 1) is a pseudo-BCK algebra.
Remark 1.
([1]) In any pseudo-BCI algebra , we can define a binary relation ‘≤’ by putting:
Proposition 1.
([13]) Let be a pseudo-BCI algebra, then X satisfies the following properties, ,
- (1)
- ;
- (2)
- ;
- (3)
- ;
- (4)
- ;
- (5)
- ;
- (6)
- ;
- (7)
- ;
- (8)
- ;
- (9)
- ;
- (10)
- ;
- (11)
- ;
- (12)
- .
Definition 2.
([13]) A subset F of a pseudo-BCI algebra X is called a filter of X if it satisfies:
- (F1)
- ;
- (F2)
- ;
- (F3)
- .
Definition 3.
([1]) By a pseudo-BCI subalgebra of a pseudo- algebra X, we mean a subset S of X that satisfies , .
Definition 4.
([12]) A pseudo-BCK algebra is called a type-2 positive implicative if it satisfies:
If X is a type-2 positive implicative pseudo-BCK algebra, then for all .
Definition 5.
([23]) Let X be a reference set. A hesitant fuzzy set A on X is defined in terms of a function that returns a subset of when it is applied to X, i.e.,
where is a set of some different values in , representing the possible membership degrees of the element . is called a hesitant fuzzy element, a basis unit of the hesitant fuzzy set.
Example 1.
Let be a reference set, , , . Then, A is considered as a hesitant fuzzy set,
Definition 6.
([13]) A fuzzy set is called a fuzzy pseudo-filter (fuzzy filter) of a pseudo-BCI algebra X if it satisfies:
- (FF1)
- , ;
- (FF2)
- , ;
- (FF3)
- , .
Definition 7.
([32]) Let X be a non-empty fixed set, a neutrosophic set A on X is defined as:
where , denoting the truth, indeterminacy and falsity membership degree of the element , respecting, and satisfying the limit: .
Definition 8.
([34]) Let X be a fixed set; a neutrosophic hesitant fuzzy set N on X is defined as
in which , denoting the possible truth membership hesitant degrees, indeterminacy membership hesitant degrees and falsity membership hesitant degrees of to the set N, respectively, with the conditions and , where , , , , , for .
Example 2.
Let be a reference set, , , . Then, A is considered as a neutrosophic hesitant fuzzy set,
Conveniently, is called a neutrosophic hesitant fuzzy element, which is denoted by the simplified symbol .
Definition 9.
([34]) Let and be two neutrosophic hesitant fuzzy sets, then:
3. Neutrosophic Hesitant Fuzzy Subalgebras of Pseudo-BCI Algebras
In the following, let X be a pseudo-BCI algebra, unless otherwise specified.
Definition 10.
A hesitant fuzzy set is called a hesitant fuzzy pseudo-subalgebra (hesitant fuzzy subalgebra) of X if it satisfies:
- (HFS2)
- , ;
- (HFS3)
- , .
Definition 11.
A neutrosophic hesitant fuzzy set is called a neutrosophic hesitant fuzzy pseudo-subalgebra (neutrosophic hesitant fuzzy subalgebra) of X if it satisfies:
- (1)
- , , ;
- (2)
- , , ;
- (3)
- , , .
Example 3.
Table 1.
→.
Table 2.
↪.
Then, is a pseudo-BCI algebra. Let:
then, N is a neutrosophic hesitant fuzzy subalgebra of X.
Considering three hesitant fuzzy sets , , by:
Therefore, is called a generated hesitant fuzzy set by function ; is called a generated hesitant fuzzy set by function ; is called a generated hesitant fuzzy set by function .
Theorem 1.
Let be a neutrosophic hesitant fuzzy set on X. Then, N is a neutrosophic hesitant fuzzy subalgebra of X if and only if it satisfies the conditions: , and , are hesitant fuzzy subalgebras of X.
Proof. Necessity:
(i) By Definition 10 and Definition 11, we can obtain that is a hesitant fuzzy subalgebra of X.
(ii) , .
Similarly, . Therefore, , and are hesitant fuzzy subalgebras of X.
Sufficiency: (i) Let . Obviously, .
(ii) Let . By Definition 10, we have , thus .
Similarly, Let ; we have .
That is, N is a neutrosophic hesitant fuzzy subalgebra of X. ☐
Theorem 2.
Let be a neutrosophic hesitant fuzzy set on X. Then, the following conditions are equivalent:
(1) is a neutrosophic hesitant fuzzy subalgebra of X;
(2) , the nonempty hesitant fuzzy level sets are subalgebras of X, where is the power set of ,
Proof.
(1)⇒(2) Suppose are nonempty sets. If , then . Since N is a neutrosophic hesitant fuzzy subalgebra of X, by Definition 11, we can obtain:
then , is a subalgebra of X.
If , then . Since N is a neutrosophic hesitant fuzzy subalgebra of X, by Definition 11, we can obtain:
Thus, , is a subalgebra of X.
Similarly, we can obtain then that is a subalgebra of X.
(2)⇒(1) Suppose that are nonempty subalgebras of X, . Let with . Let . Therefore, we have . Since is a subalgebra, we can obtain . Hence, we can obtain:
Let with . Let . Then, we have . Since is a subalgebra, we can obtain . Hence, we can obtain , . Then, we have , .
Similarly, let with ; we can obtain , .
Thus, N is a neutrosophic hesitant fuzzy subalgebra of X. ☐
Definition 12.
Let be a neutrosophic hesitant fuzzy set on X. , , , , are called generated subsets by N: , ,
where “a” appears “k” times, “*” represents any binary operation “→” or “↪” on X,
Theorem 3.
Let be a neutrosophic hesitant fuzzy set on X. If N satisfies the following conditions:
(1) , ;
(2) , ;
(3) , ;
then , .
Proof.
By Proposition 1, we can obtain ,
Thus, , .
Conversely, it is easy to check that .
Finally, we can obtain . ☐
Corollary 1.
Let be a neutrosophic hesitant fuzzy set on X. If N satisfies the following conditions:
(1) , ;
(2) , ;
(3) , ;
then , .
Theorem 4.
Let be a neutrosophic hesitant fuzzy set on X. N satisfies the following conditions:
(1) , ;
(2) , .
If , , then .
Proof:
Let . If , by Proposition 1, we can obtain:
Similarly, we can obtain:
That is, , .
Corollary 2.
Let be a neutrosophic hesitant fuzzy set on X. N satisfies the following conditions:
(1) , ;
(2) , .
If , , then .
The following example shows that may not be a filter of X.
Example 4.
Table 3.
→.
Table 4.
↪.
Then, is a pseudo-BCI algebra. Let:
then is not a filter of X. Since , but .
Theorem 5.
Let be a neutrosophic hesitant fuzzy set on X. Let X be a type-2 positive implicative pseudo-BCK algebra. If functions and are injective, then is a filter of X for all .
Proof.
(1) If X is a pseudo-BCK algebra, then by Definition 1 and Proposition 1, we can obtain .
(2) Let with . Thus, . Since functions and are injective, by Definition 5, we have:
Similarly, we can obtain . Thus, we have .
(3) Similarly, let with ; we have . ☐
This means that is a filter of X for all .
Theorem 6.
Let be a neutrosophic hesitant fuzzy set on X. Let X be a type-2 positive implicative pseudo-BCK algebra. If functions and satisfy the following identifies: ,
(1) ;
(2) ;
(3) ;
then is a filter of X for all .
Proof.
(1) If X is a pseudo-BCK algebra, by Definition 1 and Proposition 1, .
(2) Let with . We have , . By Definition 5, we have:
Similarly, we can obtain . Thus, we have .
(3) Similarly, let with ; we have .
This means that is a filter of X for all . ☐
Theorem 7.
Let be a neutrosophic hesitant fuzzy set on X and F be a filter of X. If functions and are injective, then for all .
Proof.
(1) Let . By Definition 12, we have . Since F is a filter of X and are injective, thus we can obtain and . Continuing, we can obtain . Since , thus , .
(2) Let . When , we can obtain . Similarly, we have . Thus, we have .
This means that for all . ☐
Theorem 8.
Let be a neutrosophic hesitant fuzzy set on X.
(1) If is a filter of X, then N satisfies: ,
(i) ;
(ii) .
(2) If N satisfies Conditions (i), (ii) and for all , then is a filter of X.
Proof.
(1) (i) Let with ; we have . Since is a filter, thus we can have , .
(ii) Similarly, we know that (ii) is correct.
(2) Since for all , thus . Let with ; we can obtain . By Condition (i), we have . Thus, we can obtain . Similarly, let with , by Condition (1)(ii); we can obtain .
This means that is a filter of X. ☐
4. Neutrosophic Hesitant Fuzzy Filters of Pseudo-BCI Algebras
In the following, let X be a pseudo-BCI algebra, unless otherwise specified.
Definition 13.
([22]) A hesitant fuzzy set is called a hesitant fuzzy pseudo-filter (briefly, hesitant fuzzy filter) of X if it satisfies:
(HFF1) , ;
(HFF2) , ;
(HFF3) , .
Definition 14.
A neutrosophic hesitant fuzzy set is called a neutrosophic hesitant fuzzy pseudo-filter (neutrosophic hesitant fuzzy filter) of X if it satisfies:
(NHFF1) , ;
(NHFF2) , ;
(NHFF3) , .
A neutrosophic hesitant fuzzy set is called a neutrosophic hesitant fuzzy closed filter of X if it is a neutrosophic hesitant fuzzy filter such that:
.
Example 5.
Let with two binary operations in Table 5 and Table 6. Then, is a pseudo-BCI algebra. Let:
Then, N is a neutrosophic hesitant fuzzy filter of X.
Table 5.
→.
Table 6.
↪.
Theorem 9.
Let be a neutrosophic hesitant fuzzy set on X. Then, N is a neutrosophic hesitant fuzzy filter of X if and only if it satisfies the following conditions: , , , are hesitant fuzzy filters of X.
Proof. Necessity:
If N is a neutrosophic hesitant fuzzy filter:
(1) Obviously, is a hesitant fuzzy filter of X.
(2) By Definition 14, we have , ; similarly, by Definition 14, we have . Thus, is hesitant fuzzy filter of X.
(3) Similarly, we have that is a hesitant fuzzy filter of X.
Sufficiency: If , , are hesitant fuzzy filters of X. It is easy to prove that , , satisfies Definition 14. Therefore, is a neutrosophic hesitant fuzzy filter of X. ☐
Theorem 10.
Let be a neutrosophic hesitant fuzzy set on X. Then, the following are equivalent:
(1) is a neutrosophic hesitant fuzzy filter of X;
(2) , the nonempty hesitant fuzzy level sets are filters of X, where is the power set of ,
Proof.
(1)⇒(2) (i) Suppose . Let , then . Since N is a neutrosophic hesitant fuzzy filter of X, by Definition 14, we have . Thus, .
Let with , then . Since N is a neutrosophic hesitant fuzzy filter of X, by Definition 14, we have . Thus . Similarly, let with . We have .
Thus, we can obtain that is a filter of X.
(ii) Suppose . Let , then . Since N is a neutrosophic hesitant fuzzy filter of X, we have . Thus, , .
Let with , then . Since N is a neutrosophic hesitant fuzzy filter of X, we have . Thus, , . Similarly, let with . We have .
Thus, we can obtain that is a filter of X.
(iii) We have that is a filter of X. The progress of proof is similar to (ii).
(2)⇒(1) Suppose , for all .
(i’) Let with . Let . Since is a filter of X, we have . Thus, .
Let with . Let . Since is a filter of X for all , we have . Thus, .
Similarly, let with . We can obtain .
(ii’) Let with . Let . Since is a filter of X for all , we have . Thus, .
Let with . Let . Since is a filter of X for all , we have . Thus, .
Similarly, let with ; we have .
(iii’) Similarly, we can obtain .
Therefore, is a neutrosophic hesitant fuzzy filter of X. ☐
Definition 15.
is a neutrosophic hesitant fuzzy set on X. Define a neutrosophic hesitant fuzzy set by:
where , . Then, is called a generated neutrosophic hesitant fuzzy set by hesitant fuzzy level sets and .
Theorem 11.
Let be a neutrosophic hesitant fuzzy filter of X. Then, is a neutrosophic hesitant fuzzy filter of X.
Proof.
(1) If N is a neutrosophic hesitant fuzzy filter of X, by Theorem 10, we know that are filters of X. Thus, , , , ,
(2) (i) Let with . By Theorem 9, Theorem 10 and Definition 15, we know .
Let with . By Theorem 9, Theorem 10 and Definition 15, we know . Thus, we have .
Similarly, let with ; we have .
(ii) Let with or . By Definition 15, we have or . Thus, we can obtain .
Let with or . By Definition 15, we have or . Since ; thus, we can obtain .
Similarly, let with or ; we have .
(3) We can obtain , , . The process of proof is similar to (2).
Thus is a neutrosophic hesitant fuzzy filter of X. ☐
Theorem 12.
Let be a neutrosophic hesitant fuzzy filter of X. Then, N satisfies the following properties, ,
(1) ;
(2) , ;
, ;
, ;
(3) , ;
, ;
, ;
(4) , , ;
, , .
Proof.
(1) Let with . By Proposition 1, we know (or ). If N is a neutrosophic hesitant fuzzy filter of X, by Definition 14, we have (). Thus, .
Similarly, we have .
(2) By Proposition 1, Definition 14, we know, ,
Similarly, we have, :
(3) By Definition 1 and Definition 14, with regard to the function , we can obtain, ,
Similarly, we have .
With regard to the function , we can obtain, ,
Similarly, we have .
Similarly, with regard to the function , we can obtain , .
(4) Let with . By Remark 1 and Definition 14, we can obtain:
Similarly, we can obtain .
Let with . We can obtain , , . The process of the proof is similar to the above. ☐
Theorem 13.
A neutrosophic hesitant fuzzy set is a neutrosophic hesitant fuzzy filter of X if and only if hesitant fuzzy sets satisfy the following conditions, respectively.
(1) , ;
(2) , ;
(3) , .
Proof. Necessity:
By Theorem 9, Theorem 12 and Definition 14, (1)∼(3) holds.
Sufficiency: (1) , by Proposition 1, we can obtain and . We have for all . Thus, is a hesitant fuzzy filter of X.
(2) , by Proposition 1, we can obtain ; thus, we have .
Similarly, we can have .
It is easy to obtain for all . Thus, is a hesitant fuzzy filter of X.
(3) We have that is a hesitant fuzzy filter of X. The process of the proof is similar (2).
Therefore, are hesitant fuzzy filters of X. By Theorem 9, we know that N is a neutrosophic hesitant fuzzy filter of X. ☐
Theorem 14.
Let be a neutrosophic hesitant fuzzy filter of X. Then:
where ,
Proof.
If N is a neutrosophic hesitant fuzzy filter of X:
(i) By Theorem 12, we know that for .
(ii) By Theorem 12, we know that for . By Definition 14, we have . Thus, .
(iii) Suppose that the above formula is true for ; thus, , , and we can obtain . Therefore, suppose that , , then we have . By Definition 14, we can obtain:
which complete the proof. ☐
Corollary 3.
Let be a neutrosophic hesitant fuzzy filter of X. Then:
where “*” represents any binary operation “→” or “↪” on X, ,
Theorem 15.
Let be a neutrosophic hesitant fuzzy filter of X and X be a pseudo-BCK algebra, then N is a neutrosophic hesitant fuzzy subalgebra of X.
Proof.
If is a neutrosophic hesitant fuzzy filter of X, then we can obtain ,
Similarly, we can obtain . Thus, N is a neutrosophic hesitant fuzzy subalgebra of X. ☐
Theorem 16.
Let be a neutrosophic hesitant fuzzy closed filter of X. Then, N is a neutrosophic hesitant fuzzy subalgebra of X.
Proof.
The process of proof is similar to Theorem 15. ☐
If is a neutrosophic hesitant fuzzy subalgebra of X, then N may not be a neutrosophic hesitant fuzzy filter of X.
Example 6.
Definition 16.
is a neutrosophic hesitant fuzzy set on X. Define a neutrosophic hesitant fuzzy set by ,
where , . Then, is called a generated neutrosophic hesitant fuzzy set.
A generated neutrosophic hesitant fuzzy set may not be a neutrosophic hesitant fuzzy filter of X.
Example 7.
Theorem 17.
Let X be a pseudo-BCK algebra. If X is a type-2 positive implicative pseudo-BCK algebra, then is a neutrosophic hesitant fuzzy filter of X for all .
Proof.
If X is a pseudo-BCK algebra, (1) by Definition 1 and Proposition 1, we can obtain . for all .
(2) (i) Let with or or or . Thus, we can obtain:
(ii) Let with , and , . Then, by Proposition 1 and Definition 4, we can obtain:
Therefore, we can obtain,
Similarly, we can obtain,
This means that is a neutrosophic hesitant fuzzy filter of X. ☐
Example 8.
Let with two binary operations in Table 7 and Table 8. Then, is a type-2 positive implicative pseudo-BCI algebra. Let N be a neutrosophic hesitant fuzzy set. We take as an example; thus, we have satisfy . Let , , , , , ,
Then, we can obtain that is a neutrosophic hesitant fuzzy filter of X.
Table 7.
→.
Table 8.
↪.
Theorem 18.
Let be a neutrosophic hesitant fuzzy filter of X. Then, is a filter of X for all .
Proof.
(1) Let with . Then, we have . Since is a neutrosophic hesitant fuzzy filter, thus we have . Similarly, we can get .
(2) Similarly, let with ; we have , .
This means that satisfies the conditions of Definition 2 (F1), (F2) and (F3); is a filter of X. ☐
5. Conclusions
In this paper, the neutrosophic hesitant fuzzy set theory was applied to pseudo-BCI algebra, and the neutrosophic hesitant fuzzy subalgebras (filters) in pseudo-BCI algebras were developed. The relationships between neutrosophic hesitant fuzzy subalgebras (filters) and hesitant fuzzy subalgebras (filters) was discussed, and some properties were demonstrated. In future work, different types of neutrosophic hesitant fuzzy filters will be defined and discussed.
Author Contributions
All authors have contributed equally to this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant Nos. 61573240, 61473239).
Conflicts of Interest
The authors declare no conflicts of interest.
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