1. Introduction
The study of symmetry is one of the most important and beautiful themes uniting various areas of contemporary arithmetic. Algebraic structures are useful structures in pure mathematics for learning a geometrical object’s symmetries. For example, the most important functions in ring theory are those that preserve the ring operation, which are referred to as homomorphism. Another algebraic structure viz. the theory of groups is also used to provide a broad theory of symmetry. There are various sorts of symmetries that may be studied using the theory of groups, which is already widely utilized as an algebraic tool.
The
-algebras and
-algebas are important classes of logical algebras (see [
1,
2,
3,
4] for more details). The notion of fuzzy sets and various operations on it were initially introduced by Zadeh in [
5] (see [
6,
7] for more information on fuzzy sets). Many studies have been done on fuzzy set structure. For example, fuzzy ideals in
-algebras were studied by Liu in [
8]. In [
9], Meng et al. introduced the concept of “fuzzy implicative ideals” of
-algebras while Jun [
10] gave the notion of “closed fuzzy ideals” in
-algebras. Kordi et al. studied fuzzy (p-ideals, H-ideals, BCI-positive implicative ideals) [
11], and Jun et al. [
12] considered fuzzy commutative ideals in
-algebras.
In 1998, Zhang was the first to initiate the concept of bipolar fuzzy sets [
13] as a generalization of fuzzy sets, which were introduced by Zadeh in 1965, and later, the author introduced bipolar fuzzy logic [
14]. Fuzzy sets characterize each element in a given set over a unit interval while the bipolar fuzzy sets characterize the elements over the extended interval
. Intuitionistic fuzzy sets characterize elements over the interval
such that the sum of the membership degree and non-membership degree ranges over the interval
. We refer the reader to Lee’s paper [
15] where a nice comparison between these concepts is made. In
BCH-algebras, Jun et al. [
16] investigated the ideas of bipolar fuzzy subalgebras and bipolar fuzzy closed ideals. Muhiuddin et al. [
17] established the ideas of bipolar fuzzy closed, bipolar fuzzy positive implicative, and bipolar fuzzy implicative ideals of
BCK-algebras. The concept of bipolar fuzzy a-ideals of
BCI-algebras was proposed by Lee and Jun [
18]. The ideas of doubt bipolar fuzzy subalgebras and (closed) doubt bipolar fuzzy ideals were developed, and the associated characteristics of these notions were studied by Al-Masarwah [
19]. Jana et al. [
20] proposed
-bipolar fuzzy subalgebras and
-bipolar fuzzy ideals, which were described in terms of ∈-bipolar fuzzy soft sets and
q-bipolar fuzzy soft sets of
BCK/BCI-algebras. Different aspects in bipolar fuzzy structures have been studied in different algebras by many authors (see for e.g., [
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34]). More concepts related to this study have been studied in [
35,
36,
37,
38].
Motivated by the work done in this area, and using the notion introduced by Liu et al. [
39], Al-Kadi et al. introduced, in [
40], the notion of bipolar fuzzy
-implicative ideals of a
-algebra. That is, a bipolar fuzzy set
in a
-algebra
is said to be a bipolar fuzzy
-implicative ideal if it satisfies the following assertions: (1)
, (2)
, and (3)
,
.
In this paper, we continue to study bipolar fuzzy structure of different kinds of ideals in -algebras. In fact, the notions of bipolar fuzzy (closed) BCI-positive implicative ideals and bipolar fuzzy (closed) BCI-commutative ideals of BCI-algebras are introduced. The associated characteristics of bipolar fuzzy (closed) BCI-positive implicative ideals and bipolar fuzzy ideals are considered, and several conditions are presented under which a bipolar fuzzy ideal becomes a bipolar fuzzy BCI-positive implicative ideal. Furthermore, certain conditions are given under which a bipolar fuzzy (closed) ideal is a bipolar fuzzy BCI-commutative ideal.
2. Preliminaries
In this section, we collect the following notions to develop our main results.
Definition 1. A nonempty set “” together with a binary operation “*" and a constant 0 is called a “-algebra" if it satisfies the following conditions; for all ,
- (K1)
,
- (K2)
,
- (K3)
,
- (K4)
and .
The following are true in a -algebra .
- (P1)
- (P2)
- (P3)
and
- (P4)
- (P5)
- (P6)
- (P7)
for any
(see [
3] for more details).
For brevity,
denotes a
-algebra. We remind the reader of the following definitions that are taken from [
8,
12,
41,
42].
A nonempty subset A of is called an of if it satisfies
- (I1)
,
- (I2)
.
A nonempty subset A of is called a - of if it satisfies and
- (I3)
.
A nonempty subset A of is called a - of if it satisfies and
- (I4)
.
A fuzzy set in is a map from to . A fuzzy set in is called a of if it satisfies for all ,
- (F1)
, and
- (F2)
.
A fuzzy set in is called a - of if it satisfies for all , and .
A fuzzy set in is called a - of if it satisfies for all , and .
A bipolar fuzzy set in is denoted by , where and .
Definition 2 ([
28]).
A bipolar fuzzy set in Ω is called a of Ω if it satisfies the following assertions:- (BF1)
;
- (BF2)
;
- (BF3)
.
3. Bipolar Fuzzy BCI-Positive Implicative Ideal
In this section, we begin with the following definition to obtain our results.
Definition 3. A BFS in Ω is said to be a bipolar fuzzy BCI-positive implicative ideal (BF-BCI-PII) of Ω if it satisfies and
- (BF7)
,
- (BF8)
,
.
Example 1. Consider a -algebra under the * operation defined by table:Define a BFS in Ω as: | 0 | j | k |
| −0.6 | −0.3 | −0.3 |
| 0.7 | 0.4 | 0.4 |
Then, is a BF-BCI-PII of Ω. By taking in and , we find the following.
Corollary 1. Every BF-BCI-PII is a BFI.
The converse of Corollary 1 is not true, as shown in the following example.
Example 2. Consider a -algebra under the * operation defined by table:* | 0 | j | k | l | m |
0 | 0 | 0 | 0 | 0 | 0 |
j | j | 0 | j | 0 | 0 |
k | k | k | 0 | 0 | 0 |
l | l | l | l | 0 | 0 |
m | m | l | m | j | 0 |
Define a BFS in Ω as: | 0 | j | k | l | m |
| −0.6 | −0.4 | −0.6 | −0.4 | −0.4 |
| 0.6 | 0.3 | 0.6 | 0.3 | 0.3 |
Then, is a BFI of Ω but is not a BF-BCI-PII of Ω as Definition 4. A BFS in Ω is said to be a bipolar fuzzy closed BCI-positive implicative ideal (BFC-BCI-PII) of Ω if it satisfies , , and and , .
Example 3. Consider Example 1, where is a BF-BCI-PII of Ω and , . Thus is a BFC-BCI-PII of Ω.
The following result gives the consequence of Corollary 1.
Corollary 2. Every BFC-BCI-PII is a BFI.
The converse of Corollary 2 is not true. Example 2 validates it.
Lemma 1 ([
28]).
A BFS in Ω is a BFI of Ω⇔ for all , implies and . Lemma 2 ([
28]).
A BFS in Ω is a BFI of Ω⇔ for all , implies and . Theorem 1. Let be a BFI of Ω. The following assertions are equivalent:
- (1)
is a BF-BCI-PII of Ω.
- (2)
and , .
- (3)
and , .
Proof. Let
be a
BF-BCI-PII of
. Then, for any
, we have
and
On the other hand, it follows from
and
that
Therefore
and
From (
1) and (
3), (
2) and (
4), we have
and
as required.
Suppose that
and
,
Then, we have
and
Assume that
and
for all
From
and
, we obtain
By using Lemma 1, we have
and
From (
5) and (
7), (
6) and (
8), we have
and
Hence, is a BF-BCI-PII of . □
Theorem 2. Let be a BFI of Ω. Then, is a BF-BCI-PII of Ω if for all , and .
Proof. Assume that
and
for all
. Therefore
and
From
and
, we have
and on the other hand, from
,
and
, we have
Substitute (
11), (
13) in (
9) and (
12), (
16) in (
10),
and
Thus, from Theorem 1, is a BF-BCI-PII of . □
Similarly, we can prove the following.
Corollary 3. Let be a BFI of Ω. Then is a BF-BCI-PII of Ω if for all , and .
Theorem 3. Let be a BFI of Ω. The following statements are equivalent:
- (1)
is a BF-BCI-PII of Ω.
- (2)
and , .
Proof. Let
be a
BF-BCI-PII of
. Then, from Theorem 1, for any
, we have
and
From
,
,
,
and
, we have
By using Lemma 1, we obtain
and
By using (
15) and (
17), (
16) and (
18), we obtain
and
Hence, by
, we have
and
Assume that
and
Since
and
so we have
and
By the assumption, we have
and
Hence a BF-BCI-PII of . □
Theorem 4. Let be a BFI of Ω. The following assertions are equivalent:
- (1)
in Ω is a BF-BCI-PII.
- (2)
and .
- (3)
and .
- (4)
and .
- (5)
and .
Proof. Let
in
be a
BF-BCI-PII. Then, by using Theorem 1, for any
, we have
and
Now, using
and
, we obtain
Therefore, by Lemma 2, we have
and
Assume that and for all . Now .
Therefore, by Lemma 2, we have
and
Assume that
and
for
Take
and
, so
and
trivially holds.
Assume that
and
for any
. As
So, by Lemma 1, we have
and
Thus, and . Hence, is a BF-BCI-PII of . □
Theorem 5. Let be a BFI of Ω. If and for any , then in Ω is a BF-BCI-PII of Ω.
Proof. Consider
. Substituting
a by
, then using
and
, we have
Similarly, from
and
, we have
Therefore
and
. By given hypothesis, we have
and
Thus, and . Hence, by Theorem 1, is a BF--PICI of . □
4. Bipolar Fuzzy BCI-Commutative Ideal
In this section, the concept of bipolar fuzzy BCI-commutative ideals is introduced, and several properties are investigated.
Definition 5. A BFS in Ω is said to be a bipolar fuzzy BCI-commutative ideal (BF-BCI-CI) of Ω if it satisfies and
- (BF9)
,
- (BF10)
, for all .
Example 4. Consider a -algebra where and * given by the Cayley table: Let be a BFS in Ω represented by:* | 0 | j | k | l |
0 | 0 | 0 | 0 | 0 |
j | j | 0 | 0 | j |
k | k | j | 0 | k |
l | l | l | l | 0 |
| 0 | j | k | l |
| −0.4 | −0.4 | −0.2 | −0.3 |
| 0.9 | 0.9 | 0.6 | 0.8 |
Then, by routine calculations, is a BF-BCI-CI of Ω.
Definition 6. A BFS in Ω is called a bipolar fuzzy closed BCI-commutative ideal (BFC-BCI-CI) of Ω if it satisfies , , and and , for all .
Example 5. Consider Example 4, where is a BF-BCI-CI of Ω. Also and for all . Thus, is a BFC-BCI-CI of Ω.
Theorem 6. Let be a BFI of Ω. The following statements are equivalent:
- (1)
is a BF-BCI-CI of Ω.
- (2)
and
, .
- (3)
and
, .
Proof. Let
be a
BF-BCI-CI of
. Then, for any
, we have
and
Substitute 0 for
ℏ, so we obtain
and
Assume that for
,
and
As
using
and
, So, by
, we have
. By Lemma 2, we have
and
From (
19) and (
21), (
20) and (
22), we obtain
and
Assume that for all
,
and
Since
, using
. Therefore, by Lemma 1, we have
and
Substitute (
23) in (
25) and (
24) in (
26), so
and
Hence, is a BF-BCI-CI of . □
Theorem 7. Let be a bipolar fuzzy closed ideal of Ω. Then, is a BF-BCI-CI of Ω ⇔
- (1)
,
- (2)
,
for all .
Proof. Let
be a
BF-BCI-CI of
. Since
is a
BFCI of
, so for any
,
and
. From
and
, we obtain
So, by Lemma 1, we have
and
By Theorem 6, we have
and
(⇐) Let
be a
BFCI of
satisfying the conditions
and
, for all
. From
and
, we have
. By Lemma 1, we have
and
Hence, by Theorem 6, is a BF-BCI-CI of . □
5. Conclusions
The “world of science” and its “related fields” have accomplished such complicated processes for which consistent and complete information is not always conceivable. For the last few decades, a number of theories and postulates have been introduced by many researchers to handle indeterminate constituents in science and technologies. These theories include “the theory of probability”, “interval mathematics”, “fuzzy set theory”, “neutrosophic set theory”, “intuitionistic fuzzy set theory”, “bipolar fuzzy set theory”, etc. In the present paper, we applied the bipolar fuzzy set theory to an algebraic structure called BCI-algebra where the concepts of bipolar fuzzy (closed) BCI-positive implicative ideals and bipolar fuzzy (closed) BCI-commutative ideals of BCI-algebras are introduced. Moreover, the relationship between bipolar fuzzy (closed) BCI-positive implicative ideals and bipolar fuzzy ideals is investigated, and various conditions are provided for a bipolar fuzzy ideal to be a bipolar fuzzy BCI-positive implicative ideal. Furthermore, conditions are presented for a bipolar fuzzy (closed) ideal to be a bipolar fuzzy BCI-commutative ideal. Finally, the relationships among bipolar fuzzy BCI-implicative ideals, bipolar fuzzy BCI-positive implicative ideals and bipolar fuzzy BCI-commutative ideals are investigated. In future work, one may extend these concepts to various algebras BL-algebras, MTL-algebras, R0-algebras, MV-algebras, EQ-algebras, lattice implication algebras, etc.