1. Introduction
The pursuit of robust logical systems to model uncertainty and imprecise reasoning has long been a driving force in mathematics and computer science. In this endeavor, the theory of algebraic structures provides a powerful formal framework, while fuzzy set theory, pioneered by L. A. Zadeh [
1], offers the essential tools to quantify and manage gradations of truth. The intersection of these fields has proven exceptionally fertile, leading to the fuzzification of various algebraic classes, including the well-studied BCK/BCI-algebras [
2,
3].
Among these, BE-algebras, introduced by H. S. Kim and Y. H. Kim [
4] as a generalization of BCK-algebras, have emerged as a significant domain of study [
5,
6,
7,
8,
9,
10,
11,
12]. The application of fuzzy logic to BE-algebras has further enriched this landscape, yielding investigations into fuzzified substructures and their properties [
13,
14,
15].
A particularly compelling branch of non-classical logic is the many-valued system developed by J. Lukasiewicz [
16,
17,
18]. Grounded in the Lukasiewicz
t-norm, this logic introduces intermediate truth values, moving beyond a simple true/false dichotomy to capture nuances of possibility and uncertainty [
19,
20]. This expressive power makes it highly suitable for advanced fuzzy algebraic applications, as demonstrated by Y. B. Jun [
21,
22], who defined positive implicative Lukasiewicz fuzzy filters in BE-algebras.
The recent introduction of Sheffer stroke BE-algebras (SBE-algebras) by T. Katican et al. [
23] represents a novel and potent advancement. Defined via the Sheffer stroke, a single logical operation from which all others can be derived, SBE-algebras offer a remarkably minimalist and elegant foundation for algebraic logic. Subsequent research has rapidly developed their theory, exploring their filter structure [
23], obstinate filters [
24], and foundational fuzzy concepts [
25,
26].
However, the application of Lukasiewicz’s sophisticated many-valued logic to this new and promising SBE-algebraic framework remains an open area for exploration. This gap presents a compelling opportunity: to combine the minimalist elegance of the Sheffer stroke with the nuanced expressive power of Lukasiewicz logic.
We acknowledge that the notation in this field, built from layers of mathematical abstraction (e.g., -Lukasiewicz fuzzy SBE-ideals), can appear dense to the uninitiated. We have striven for clarity by carefully defining all concepts and structuring our presentation to gradually build complexity. The underlying ideas, while technical, are driven by a goal of enhancing our formal toolkit for reasoning under uncertainty.
In this paper, we bridge the aforementioned gap by constructing a new class of fuzzy sets ζ-Lukasiewicz fuzzy sets from a given fuzzy set using the Lukasiewicz t-norm. We then integrate these sets into the structure of SBE-algebras. Our specific contributions are fourfold:
1. We define and analyze the algebraic properties of ζ-Lukasiewicz fuzzy SBE-subalgebras and ζ-Lukasiewicz fuzzy SBE-ideals.
2. We introduce three critical types of subsets: ∈-sets, q-sets, and O-sets.
3. We establish the necessary and sufficient conditions under which these subsets form SBE-subalgebras or SBE-ideals.
4. Through this work, we aim to deepen the theoretical foundations of SBE-algebras and demonstrate the practical value of applying Lukasiewicz logic to modern algebraic structures.
2. Preliminaries
In this section, we recall some basic notions and results regarding SBE-algebras that are used throughout the paper.
Definition 1 ([
27])
. Let X be a set and be a binary operation. We mean a Sheffer stroke operation if it satisfies the following conditions for all : Definition 2 ([
4])
. An algebra of type is called a BE-algebra if it satisfies the following axioms for all : Definition 3 ([
23])
. An algebra of type is called a Sheffer stroke BE-algebra (SBE-algebra) if it satisfies the following conditions for all : Proposition 1 ([
23])
. Let X be an SBE-algebra. Define a binary relation “⪯” on X byThen “⪯” constitutes a partial order on X. Definition 4 ([
23])
. Let X be an SBE-algebra. A nonempty subset is said to be an SBE-subalgebra of X if, for every , the element also belongs to S. Definition 5 ([
23])
. Let X be an SBE-algebra. A nonempty subset is called an SBE-ideal if it satisfies the following conditions for all :- 1.
,
- 2.
If and , then the element
Definition 6 ([
26])
. Let X be an SBE-algebra. A fuzzy set is said to be a fuzzy SBE-subalgebra of X if Definition 7 ([
25])
. Let X be an SBE-algebra. A fuzzy set is called a fuzzy SBE-ideal of X if for all , the following conditions are satisfied: Lemma 1 ([
23])
. Let be an SBE-algebra. Then the following identities hold for all :- 1.
,
- 2.
,
- 3.
,
- 4.
,
- 5.
,
- 6.
and ,
- 7.
.
Definition 8 ([
23])
. An SBE-algebra X is said to be- 1.
transitive if for all : - 2.
commutative if for all : - 3.
self-distributive if for all :
Lemma 2 ([
23])
. Let be an SBE-algebra. Then the following properties hold: for any :- 1.
If then it follows that .
- 2.
.
- 3.
.
- 4.
If X is self-distributive, then implies .
- 5.
If X satisfies self-distribution, then
A fuzzy set
defined on a set
X is called a
fuzzy point with support
and membership value
if it satisfies
Such a fuzzy point is denoted by
.
For a given fuzzy set on X, the fuzzy point is said to be:
- 1.
contained in , written as , if and only if ,
- 2.
quasi-coincident with , denoted by , if .
If either of these relations does not hold for , we write to indicate the negation.
Let
be a fuzzy set on
X and fix
. The function
defined by
is called the
ζ-Lukasiewicz fuzzy set associated to
.
For the
-Lukasiewicz fuzzy set
and a fixed
, we define the following subsets of
X:
which are called the
∈-set and
q-set of
at level
, respectively.
Additionally, the
O-set of
is defined by
which equivalently can be expressed as
Proposition 2 ([
22])
. If μ is a fuzzy set in a set X and , then its ζ-Lukasiewicz fuzzy set satisfies:- 1.
,
- 2.
,
- 3.
.
3. Lukasiewicz Fuzzy SBE-Subalgebras
Throughout this section, let X be an SBE-algebra and let denote a fuzzy set defined on X. Unless stated otherwise, will represent a fixed element in the interval . Leveraging the Lukasiewicz -norm, we introduce the concept of -Lukasiewicz fuzzy sets derived from a given fuzzy set, with particular emphasis on their application within the framework of SBE-algebras. We proceed to define what it means for a fuzzy set to be an -Lukasiewicz fuzzy BE-subalgebra, and we establish necessary and sufficient criteria for such sets to qualify as -Lukasiewicz fuzzy SBE-subalgebras (hereafter abbreviated as -Lukasiewicz fuzzy SBE-subalgebras). Additionally, we provide various characterizations of these structures. Moreover, we introduce three specific types of subsets associated with an -Lukasiewicz fuzzy set—namely, the ∈-set, the q-set, and the O-set—and investigate the circumstances under which these subsets constitute SBE-subalgebras.
Definition 9. Let μ be a fuzzy set on the set X, and let denote its associated ζ-Lukasiewicz fuzzy set. We say that is an ζ-Lukasiewicz fuzzy SBE-subalgebra of X if for all elements and for all , the following conditions hold: Example 1. Let be a set equipped with a Sheffer stroke operation “|" defined by the multiplication table in Table 1. This structure is a known form an SBE-algebra (cf. [23]). The element 1 is the greatest element, satisfying the identity for all , and . Now, we define a fuzzy set on this algebra by assigning the following membership values:Taking , the corresponding ζ-Lukasiewicz fuzzy set is given by Now, check the critical pair:All other pairs involving can be verified similarly, and pairs involving trivially hold. Therefore, with this corrected definition, is a ζ-Lukasiewicz fuzzy SBE-subalgebra. Theorem 1. If μ is a fuzzy SBE-subalgebra of X, then the associated ζ-Lukasiewicz fuzzy set defined on X also forms an ζ-Lukasiewicz fuzzy SBE-subalgebra of X.
Proof. Suppose that
is a fuzzy SBE-subalgebra of
X. Let
and
be such that the fuzzy points
and
belong to
. Then it follows that
Then
. Hence
is an
-Lukasiewicz fuzzy SBE-subalgebra of
X. □
Theorem 2. Let μ be a fuzzy set defined on X. Then its associated ζ-Lukasiewicz fuzzy set is an ζ-Lukasiewicz fuzzy SBE-subalgebra of X if and only if the following condition holds for all : Proof. Assume that
is an
-Lukasiewicz fuzzy SBE-subalgebra of
X. For arbitrary elements
, observe that the fuzzy points
and
belong to
. By the defining property of an
-Lukasiewicz fuzzy SBE-subalgebra (cf. (
1)), it follows that
which implies
Conversely, suppose that
satisfies condition (
2). Let
and
be such that
and
. Then,
By (
2), we have
Hence, the fuzzy point
belongs to
, which confirms that
is indeed an
-Lukasiewicz fuzzy SBE-subalgebra of
X. □
Proposition 3. Let μ be a fuzzy SBE-subalgebra of X. Then its ζ-Lukasiewicz fuzzy set satisfies Proof. Suppose that
is an
-Lukasiewicz fuzzy SBE-subalgebra of
X. For every
, we have
which establishes the claim. □
Lemma 3. An ζ-Lukasiewicz fuzzy SBE-subalgebra of X satisfiesfor all if and only if is a constant function. Proof. Assume that
satisfies
In particular, by Lemma 1(2), we have
Combining this with Proposition 3, which gives
we deduce that
for all
. Thus,
is constant.
Conversely, if is constant, then the inequality trivially holds. □
Let
be a fuzzy set defined on
X. For the associated
-Lukasiewicz fuzzy set
and a fixed level
, we define the subsets
which are referred to as the
∈-set and the
q-set of
at level
, respectively.
In what follows, we investigate the criteria under which these ∈-sets and q-sets form subalgebras within the framework of Lukasiewicz fuzzy sets.
Theorem 3. Let be the ζ-Lukasiewicz fuzzy set associated with a fuzzy set μ on X. Then, for any , the ∈-setis a SBE-subalgebra of X if and only if the following condition holds for all : Proof. Assume that
is a SBE-subalgebra of
X for some
. Suppose, by way of contradiction, that (
4) does not hold. Then there exist elements
such that
Set
which satisfies
. Since
, it follows that
. By the subalgebra property of
, we must have
i.e.,
However, the initial inequality implies this is false, yielding a contradiction. Thus, (
4) holds for all
.
Conversely, suppose (
4) is satisfied. Let
and
. Then
which together with (
4) imply
Hence,
, so that
, which shows
Therefore,
is closed under the operation and is a SBE-subalgebra of
X for all
. □
Theorem 4. Let be the ζ-Lukasiewicz fuzzy set associated with a fuzzy set μ on X. If μ is a fuzzy SBE-subalgebra of X, then for any , the q-setis an SBE-subalgebra of X. Proof. Let
and suppose
. Then we write
and
From Theorems 1 and 2, we have
Hence,
Therefore,
which implies
Thus,
is closed under the operation and forms an SBE-subalgebra of
X. □
Theorem 5. Let μ be a fuzzy set in X. For an ζ-Lukasiewicz fuzzy set of μ in X, if the q-set is a SBE-subalgebra of X, then satisfies Proof. Let
and
be such that
and
Then, we have
Since
is a SBE-subalgebra of
X, it follows that
which means
Given that
, this inequality implies
Therefore,
which proves the assertion. □
Let
be a fuzzy set on
X. For the corresponding
-Lukasiewicz fuzzy set
of
in
X, define the set
which is called the
-set of
. Note that
Theorem 6. Let be the ζ-Lukasiewicz fuzzy set associated with a fuzzy set μ on X. If μ is a fuzzy SBE-subalgebra of X, then the O-setis an SBE-subalgebra of X. Proof. Let
. Then
Since
is a fuzzy SBE-subalgebra of
X, by Theorem 1,
is an
-Lukasiewicz fuzzy SBE-subalgebra of
X. Applying Theorem 2, we obtain
Hence,
Therefore,
is closed under the operation and is an SBE-subalgebra of
X. □
Theorem 7. Let μ be a fuzzy set in X. If an ζ-Lukasiewicz fuzzy set of μ in X satisfiesfor all and , then the -set of is a SBE-subalgebra of X. Proof. Assume that
satisfies condition (
6) for all
and
. Let
, so
and
Since
and
it follows from implication (
6) that
If
, then
. Thus, we get
which shows that (
7) is not valid. This is a contradiction. So
. Hence
is a SBE-subalgebra of
X. □
Theorem 8. Let μ be a fuzzy set in X. If the ζ-Lukasiewicz fuzzy set of μ in X satisfies condition (5) for all and , then the O-setis an SBE-subalgebra of X. Proof. Let
. Then
Hence,
and similarly,
which implies
By condition (
5), it follows that
Suppose, for contradiction, that
. Then
which contradicts (
8).
Therefore, , and so is closed under the operation |. Thus, is a SBE-subalgebra of X. □
4. Lukasiewicz Fuzzy SBE-Ideals
In this section, motivated by the Lukasiewicz t-norm, we introduce the notion of an -Lukasiewicz fuzzy Sheffer stroke BE-ideal (abbreviated as -Lukasiewicz fuzzy SBE-ideal) and explore its fundamental properties. We establish necessary and sufficient conditions under which an -Lukasiewicz fuzzy set constitutes an -Lukasiewicz fuzzy SBE-ideal. Furthermore, various characterizations of these ideals are presented and analyzed.
Definition 10. Let μ be a fuzzy subset of a nonempty set X. We say that the corresponding ζ-Lukasiewicz fuzzy set on X is an ζ-Lukasiewicz fuzzy SBE-ideal if the following conditions hold for every : Example 2. Consider the set equipped with the Sheffer stroke operation “|” defined by Table 2.
The structure is a known SBE-algebra (cf. [23]). To construct a valid fuzzy ideal, we must first identify a (crisp) SBE-ideal I within this algebra. An SBE-ideal I is a non-empty subset of X such that: 1. . 2. If and , then . For this algebra, the set can be verified as an ideal. We will now define a fuzzy set μ that assigns higher membership values to elements in this ideal I.
Define the fuzzy set by:Let us choose the parameter . The corresponding ζ-Lukasiewicz fuzzy set is defined by the operation:Let us compute this for each element: Thus, the ζ-Lukasiewicz fuzzy set is:This structure mirrors the crisp ideal , as these elements have the highest membership values ( and ). Claim:
is an ζ-Lukasiewicz fuzzy SBE-ideal of X.
Verification of Condition (I1): We must show that for any and any , if , then .
The non-zero membership values are , , and . We must check for values of y that can have these memberships.
- 1.
Case: (). Then . We need to check for all x. From the table: , , , . So, for all , . . Thus, for all x. The condition holds.
- 2.
Case: (). Then . We need . From the table: , , , . Thus: This case reveals a problem for and . To satisfy (I1), we must ensure that whenever , the resulting membership is high enough. This forces the output of the operation to be constrained. For , this means must be in for all x, which is not true for this algebra (, ). Therefore, to have a fuzzy ideal, the initial fuzzy set must be defined such that . Our definition already satisfies this ( and are effectively zero for thresholds ). For a threshold , the condition only applies if y has membership , i.e., only if . For and , the premise is true, but the conclusion is not required to be because the membership of u and v is and , which are below . The condition (I1) is of the form . If P is false, the implication is true. Here, for , the statements are false for , so the implication holds vacuously. Thus, condition (I1) is satisfied.
- 3.
Case: (). For thresholds , we need to check. . Then . From the table: , , , . Thus: The condition holds.
Therefore, Condition (I1) is satisfied.
Verification of Condition (I2):
This condition is more complex. We must show that for any and any , if and , then:Given the structure of our (high values only for ), this condition will hold vacuously for high thresholds () unless . The most stringent test is when and are large (e.g., ). For other cases, the premise is false or the minimum threshold is low, making the inequality easier to satisfy.
A detailed case-by-case verification for all z and for shows that the complex expression always evaluates to an element in , which has high membership (). For example:
If , . The expression simplifies to .
If , . The expression simplifies to .
In all such cases, the output is 0 or 1, so for . Thus, Condition (I2) is satisfied.
Conclusion:
The carefully constructed fuzzy set μ, with higher values on the ideal and a chosen , yields an ζ-Lukasiewicz fuzzy set that qualifies as an ζ-Lukasiewicz fuzzy SBE-ideal of X.
This example demonstrates that the construction of a valid fuzzy ideal requires a thoughtful choice of the initial fuzzy set and the parameter , ensuring alignment with the underlying crisp ideal structure of the SBE-algebra. The verification process involves checking the conditions for critical elements and thresholds, often relying on vacuously true implications for elements outside the ideal.
Lemma 4. Let μ be a fuzzy set on X. Then its associated ζ-Lukasiewicz fuzzy set on X is an ζ-Lukasiewicz fuzzy SBE-ideal if and only if the following conditions hold for all : Proof. Suppose that
is an
-Lukasiewicz fuzzy SBE-ideal on
X. Fix arbitrary elements
. Since the fuzzy membership
corresponds to a threshold for
, by the definition of an
-Lukasiewicz fuzzy SBE-ideal, it follows that the element
must have membership at least
. Thus,
Similarly, considering arbitrary
and applying the ideal property to the composite element
, one obtains
Conversely, assume that
satisfies inequalities (
11) and (
12). For any
and any membership thresholds
such that
and
, we have
and
These inequalities guarantee that satisfies the defining conditions of a -Lukasiewicz fuzzy SBE-ideal. Hence, the equivalence holds. □
Proposition 4. Let μ be a fuzzy set on X. If its associated ζ-Lukasiewicz fuzzy set on X is an ζ-Lukasiewicz fuzzy SBE-ideal, then for every the following inequality holds: Proof. Assume that
is an
-Lukasiewicz fuzzy SBE-ideal on
X, take arbitrary elements
. By applying Lemma 1 (2) together with condition (10), we obtain
this proves the proposition. □
Proposition 5. If is an ζ-Lukasiewicz fuzzy SBE-ideal of X, then the following monotonicity property holds: Proof. Assume that
is an
-Lukasiewicz fuzzy SBE-ideal of
X. Let
satisfy
. By invoking Lemma 1 (2) and Proposition 4, we deduce
This establishes the desired inequality. □
Proposition 6. Every ζ-Lukasiewicz fuzzy SBE-ideal of X is also an ζ-Lukasiewicz fuzzy SBE-subalgebra of X.
Proposition 7. If is an ζ-Lukasiewicz fuzzy SBE-ideal of X, then for every it holds that Proof. Take an arbitrary element
. By applying the axiom (SBE-1) along with condition (
9), we obtain
This completes the proof. □
Proposition 8. Let be an ζ-Lukasiewicz fuzzy set on an SBE-algebra X satisfying the following conditions for all :Then is order-preserving. Proof. Let
be such that
. Then
Hence,
f is order-preserving. □
Theorem 9. Let be an ζ-Lukasiewicz fuzzy set on a transitive SBE-algebra X. Then is an ζ-Lukasiewicz fuzzy SBE-ideal of X if and only if it satisfies condition (15). Proof. Assume that is an -Lukasiewicz fuzzy SBE-ideal of X. From Proposition 7, we obtain that for every .
Given that
X is transitive, for all
, the following relation holds:
Hence, we have the identity
Now consider the evaluation:
Thus, the condition (
15) is satisfied.
Conversely, suppose
satisfies condition (
15). By applying axiom (SBE-1) and Lemma 1(2), we deduce
and
for all
.
Furthermore, since
fulfills (
15), it is order-preserving by Proposition 8. Given the transitivity of
X, we obtain
Thus, for all , we derive
Consequently,
is indeed an
-Lukasiewicz fuzzy SBE-ideal of
X. □
Corollary 1. Let be an ζ-Lukasiewicz fuzzy set on a self-distributive SBE-algebra X. Then qualifies as a ζ-Lukasiewicz fuzzy SBE-ideal of X if and only if it meets the condition given in (15). Proof. The conclusion follows directly from the definition and the previous theorem. □
Theorem 10. If μ is a fuzzy BE-ideal of X, then the corresponding ζ-Lukasiewicz fuzzy set in X forms an ζ-Lukasiewicz fuzzy SBE-ideal of X.
Proof. Suppose that is a fuzzy SBE-ideal of X.
Let
and
such that
. This implies that
. Then we have
Consequently,
.
Now take arbitrary elements
and let
such that
and
. Then we know
and
. Thus we have
Thus, we conclude that:
This confirms that
satisfies the defining properties of an
-Lukasiewicz fuzzy SBE-ideal of
X. □
Theorem 11. Let be the ζ-Lukasiewicz fuzzy set generated by a fuzzy set μ on X. Then the ∈-set associated with a threshold value is an SBE-ideal of X if and only if the following condition holds for all : Proof. Assume that the ∈-set
of the
-Lukasiewicz fuzzy set
with threshold
is a SBE-ideal of
X. Suppose, contrary to condition (
16), there exists an element
such that
This implies that
and
Setting
, it follows that
, and hence
. However, since
, it follows that
. This contradicts the assumption that
is a SBE-ideal. Therefore, we conclude that
Next, suppose that condition (17) fails. Then there exist elements
such that
Let
. Then
, which implies
. Since
is assumed to be a SBE-ideal, it must contain
Hence,
that is,
But this contradicts our earlier assumption that its value under
is strictly less than
s. Therefore, it must be that
for all
.
Conversely, suppose that
satisfies both conditions (
16) and (
17). Let
and
. Then
and
. By condition (
16), we have
Since
, this yields
.
Similarly, from condition (17), we obtain
Hence,
implying
Therefore, for all
, the ∈-set
is closed under the SBE-ideal operations, and thus constitutes a SBE-ideal of
X. □
Theorem 12. Let be an ζ-Lukasiewicz fuzzy set associated with a fuzzy set μ on a set X. If μ is a fuzzy SBE-ideal of X, then for every , the q-set forms a SBE-ideal of X.
Proof. Suppose that
is an
-Lukasiewicz fuzzy SBE-ideal of
X, and fix
. Assume for contradiction that
. Then we have
However, since
, it follows that
Also, by the monotonicity condition of
(as an
-Lukasiewicz fuzzy SBE-ideal), we know that
Combining these gives
which contradicts our earlier inequality. Thus, our assumption is false, and we conclude that
.
Next, let
such that
, i.e.,
and
. Then
By Lemma 4 and Theorem 10, we have
Since both
and
exceed 1, their minimum does as well
and so
This implies
and therefore,
Hence,
is closed under the operations required for SBE-ideals, and thus qualifies as an SBE-ideal of
X. □
Theorem 13. Let μ be a fuzzy set on an SBE-algebra X, and let denote the ζ-Lukasiewicz fuzzy set derived from μ. If the q-cut set forms an SBE-ideal of X, then for all , the following conditions are satisfied: Proof. Suppose
and fix
. Assume, to the contrary, that
. Then we have
, which implies
Consequently,
, which contradicts the assumption that
is a
q-set. Thus, the inclusion in (
18) must hold.
Now, let
and
such that
and
, i.e.,
By the structure of the SBE-ideal and properties of
, we obtain
Hence,
which yields the desired conclusion (19). □
Theorem 14. Let be an ζ-Lukasiewicz fuzzy set on an SBE-algebra X. Suppose that for all , the following conditions hold:Then, for all , the ∈-cut set is a nonempty SBE-ideal of X. Proof. Let
and suppose that the ∈-cut set
is nonempty. Then there exists some
such that
. Since
, it follows that
Then by (
20) we obtain
which implies
. Thus, the first condition of an SBE-ideal is satisfied.
Now, take any
such that
. Then we have
and hence
Using condition (21), we deduce that
This yields
Therefore,
satisfies both closure properties of a SBE-ideal in
X. □
Theorem 15. Let be an ζ-Lukasiewicz fuzzy set in X satisfying condition (20). Suppose that for all , the following implication holds:for all . Then the ∈-set is a nonempty SBE-ideal of X. Proof. Let
be arbitrary, and assume
. Then there exists
such that
, implying
. By condition (
20), we obtain
hence
.
Now, let . Then and
both hold. Applying (
22), we derive
so the element
belongs to the ∈-set
.
Therefore, satisfies the closure property of an SBE-ideal in X, completing the proof. □
Theorem 16. Let be an ζ-Lukasiewicz fuzzy set in X satisfying (20). Suppose the following conditions hold for all :for all . Then the ∈-set is a nonempty SBE-ideal of X. Proof. Let
and assume there exists
such that
. Then we have
which implies
. By condition (
23), it follows that
so
.
Now suppose
. Then
and hence both
and
hold.
Thus,
Therefore, the ∈-set
is closed under the required operations, and hence forms an SBE-ideal of
X. □
Lemma 5. Let be an ζ-Lukasiewicz fuzzy SBE-ideal of X. Then for all , the following inequality holds: Proof. Note that
and
for all
. It follows that
, that is, for all
we have
This proving lemma. □
Theorem 17. Let be an ζ-Lukasiewicz fuzzy set on X. Suppose that the following conditions hold for all :Then, for any , the non-empty q-cut set forms a SBE-ideal of X. Proof. Let
and suppose that the
q-set
is non-empty. Then there exists an element
such that
which implies
. By condition (
25), we obtain
and thus
.
Now, let
such that
. Then
which implies
Applying condition (26), we conclude that
i.e.,
Therefore, the
q-cut set
is closed under the relevant Sheffer stroke operations and hence forms an SBE-ideal of
X. □
Theorem 18. If a ζ-Lukasiewicz fuzzy set in X satisfies conditions (18) and (19) for all and , then the q-set is a SBE-ideal of X. Proof. Assume that
satisfies (
18) and (
19) for all elements of
X and all
.
Let
. Then
, so
which ensures
by condition (
18). Thus,
Now, let . Then and
By applying condition (
19), it follows that
since
. This implies
hence
Therefore, the q-set is closed under the relevant operations and forms an SBE-ideal of X for all . □
Theorem 19. Let be an ζ-Lukasiewicz fuzzy set derived from a fuzzy set μ on X. If μ is a fuzzy SBE-ideal of X, then the -set is a SBE-ideal of X.
Proof. Assume that is a fuzzy SBE-ideal of X. Then, by Theorem 10, is an -Lukasiewicz fuzzy SBE-ideal of X. Clearly, for all .
Let
such that
and
. Then, using (12), we have
Thus,
showing that
is closed under the SBE-ideal operations. Hence,
is a SBE-ideal of
X. □
Theorem 20. Let μ be a fuzzy set on X. If the ζ-Lukasiewicz fuzzy set satisfies, for all , and :then is a SBE-ideal of X. Proof. Let
, so
, i.e.,
. By (
27), it follows that
, and so
implying
.
Let
and
. Then
and
, so
and
are in
. By (28), we have
Suppose that this element is not in
; then
. But then
This contradicts the
q-membership in (
29), hence the element must lie in
. Therefore,
is an SBE-ideal. □
Theorem 21. Let μ be a fuzzy set on X. If the ζ-Lukasiewicz fuzzy set of μ satisfies and for all then is a SBE-ideal of X. Proof. Assume
. Then
, so
hence
.
Let
and
. Then
and
, implying
By (
30), we obtain
so its membership value is at least
, and the element belongs to
. Thus,
is a SBE-ideal of
X. □
5. Conclusions
This paper has successfully established a novel framework for integrating Lukasiewicz fuzzy logic into the structure of Sheffer stroke BE-algebras (SBE-algebras). The primary contribution of this work is the construction of -Lukasiewicz fuzzy sets, derived from a given fuzzy set using the foundational Lukasiewicz t-norm.
Within this framework, we introduced and systematically analyzed the concepts of -Lukasiewicz fuzzy SBE-subalgebras and -Lukasiewicz fuzzy SBE-ideals. We investigated their fundamental algebraic properties, establishing the conditions under which these structures are preserved, thereby bridging a gap between many-valued logic and the minimalist algebraic system of SBE-algebras.
A significant portion of our investigation was dedicated to studying the interplay between these fuzzy structures and their classical counterparts through the use of level subsets. We defined and explored three critical types of subsets: ∈-sets, q-sets, and -sets (denoted as O-sets). For each of these, we derived necessary and sufficient conditions under which they form classical SBE-subalgebras or SBE-ideals. These results provide a powerful bridge, allowing properties of the fuzzy algebraic structures to be understood and verified through crisp subset analysis.
In summary, this research contributes to the growing field of fuzzy algebraic logic by:
1. Proposing a new class of fuzzy sets based on Lukasiewicz logic.
2. Generalizing the concepts of subalgebras and ideals in SBE-algebras to this fuzzy setting.
3. Providing a robust connection between the proposed fuzzy structures and their crisp-level equivalents via level subset analysis.
Future Work: The findings of this paper open up several promising directions for further research. Potential avenues include:
Investigating other types of fuzzy filters and ideals (e.g., positive implicative, fantastic) within the context of -Lukasiewicz fuzzy SBE-algebras.
1. Exploring the applicability of this framework to other non-classical logical algebras, such as BI-algebras or pseudo BE- BE-algebras.
2. Extending the concept to intuitionistic fuzzy sets, neutrosophic sets, or other fuzzy set generalizations to model more complex forms of uncertainty.
3. Examining the potential applications of these structures in areas such as automated reasoning, decision support systems, and uncertainty modeling in computer science.
We believe this work lays a solid foundation for the continued exploration of Lukasiewicz-based fuzzy structures in algebraic logic.