1. Introduction
In today’s world, the mathematical modeling and manipulation of various kinds of uncertainties has turned into a growing concern in the solution of difficult problems in a variety of fields, such as engineering, environmental science, economics, social sciences, and medicine. Even though probability theory, fuzzy set theory [
1], rough set theory [
2], and interval mathematics [
3], and so on, are well-known and effective tools for dealing with ambiguity and uncertainty, each has its own set of limitations; a common major weakness among these mathematical techniques is the limitation of parametrization tools.
In 1999, Molodtsov [
4] originated the soft set theory as a mathematical tool for dealing with uncertainty, which is free of the challenges related to the earlier mentioned theories. Soft sets were presented as a collection of parameterized possibilities of a universe. The characteristics of parameter sets associated with soft sets provide a standardized foundation for modeling uncertainty. This led to the rapid growth of soft set theory and its relevant areas in a short amount of time and provided various applications of soft sets in real life, such as medical diagnosis [
5,
6], evaluation of nutrition systems [
7], decision making [
8], analysis of networks [
9], and information systems [
10,
11]. To face more complicated problems, some extensions of soft sets were embraced, such as bipolar soft sets and double-framed soft sets, and their efficiency to address practical problems was demonstrated, as illustrated in [
12,
13].
Multiple researchers applied soft set theory to various mathematical structures such as soft group theory [
14], soft ring theory [
15], soft category theory [
16], soft topology [
17,
18,
19,
20], infra-soft topology [
21], N-soft topology [
22], soft topological soft groups and soft rings [
23,
24], etc.
An algebra of subsets of a universal (ordinary) set is crucial for the growth of several disciplines, including mathematical analysis, probability theory, and economics and finance. The concept of algebras of soft settings was established by Riaz et al. [
25]. Various properties and relations of soft algebras remain untouched. Therefore, we further study this concept and establish a general construction for producing soft algebras. This construction helps us to study the properties of soft algebras by means of the properties of ordinary algebras.
The content of the paper is arranged as follows: We provide a summary of the background on soft set theory and probability theory in
Section 2.
Section 3 concentrates on the study of soft semi-algebras and soft algebras, with their relationships. Then, it investigates some operations on soft algebras.
Section 4 uses two remarkable formulas to demonstrate the relationships between ordinary and soft algebras.
Section 5 discusses the application of representing weather conditions using elements of the generated soft algebra. We end with a brief conclusion and discussion (
Section 6).
3. Soft Semi-Algebras and Soft Algebras
Definition 11. A family is called a soft semi-algebra on X if it satisfies the following properties:
- 1.
are in ,
- 2.
if are in , then is in , and
- 3.
if , where are in and for , then is in .
Let us recall the definition of a soft algebra.
Definition 12 ([
25]).
A family is said to be a soft algebra on X if Σ meets the following properties:- 1.
is in Σ,
- 2.
if is in Σ, then is in Σ, and
- 3.
if is in Σ, for all , then is in Σ.
If (3) in the above definition holds true for countably infinite members of
, then
will be called a soft
-algebra on
X (see [
34]).
Example 1. The collections and are trivially soft algebras. They are, respectively, the smallest and the largest soft algebras.
Example 2. For any , is a soft algebra.
Readily, each soft -algebra is a soft algebra and each soft algebra is a soft semi-algebra, but not the converse.
Example 3. Let X be an infinite universal set and be a set of parameters. The collectionwill be a soft algebra. On the other hand, Σ is not a soft σ-algebra. Example 4. Let be the set of real numbers and let . The collectionis a soft semi-algebra but not a soft algebra. Lemma 1. Let be an indexed family of soft algebras on X with an index set I. Then is a soft algebra.
Proof. Since each soft algebra contains , so is not null and it contains . Let . Then for each , and therefore, for each . Hence, . For the same reason, is closed under the finite soft unions. □
On the other hand, the union of two soft algebras need not be a soft algebra.
Example 5. Let and let . Given the following two soft algebras: and , where , , , and . Then is not a soft algebra.
However, the next result demonstrates that the union of soft algebras is a soft algebra under certain conditions.
Theorem 1. Let be a countable family of soft algebras on X. If , then is a soft algebra.
Proof. Since is a soft algebra for all , then . Thus, . Let . Then for some n and so as is a soft algebra. Surely, . Suppose . Since , then there exists some such that . Thus, as is a soft algebra and hence, . □
It is worth noting that the above result does not hold true for soft -algebras. Let and be a set of parameters. If is the collection of all soft subsets of with their complements, where , then is an increasing collection of soft algebras. Then is a soft algebra mentioned in Example 3, which is not a soft -algebra.
Lemma 2. Let be a subcollection of . Then there exists a unique soft algebra Σ on X containing , in the sense that if is any other soft algebra containing , then .
Proof. Since is a soft algebra containing , so such a soft algebra always exists. Therefore, the soft algebra obtained in Lemma 1 is the required soft algebra. □
We refer to the above soft algebra as the soft algebra on X generated by and denote it by . If is a countable collection, then is called the countably generated soft algebra. The soft algebra considered in Example 2 is the soft algebra generated by .
Theorem 2. Let , for , and let Σ be any soft algebra on X. The soft algebra generated by possesses the below properties:
- 1.
.
- 2.
.
- 3.
is a soft algebra if .
- 4.
implies .
- 5.
.
- 6.
implies .
Proof. - (1)
It follows from the definition of .
- (2)
The first direction, , follows from (1). Now, we always have , so is a soft algebra including . Since is the smallest soft algebra including . Thus, . Hence, .
- (3)
Straightforward.
- (4)
By (1), . Since , then and so is a soft algebra containing , but is the smallest soft algebra containing . Thus, .
- (5)
We only prove the last equality, other inclusions can be concluded easily. Since , by (4), . Similarly, . Therefore, . By (4), .
On the other hand, since and , then . By (4), . Hence, .
- (6)
It follows from (2) and (4).
□
Proposition 1. Let be a soft semi-algebra on X. The familyis a soft algebra on X and , where the symbol means disjoint soft union. Proof. The second claim
is obvious, because each
. It remains to show that
is a soft algebra. Clearly
as
. Let
. By definition,
Since for all i and j, and is closed under finite soft intersections, therefore, .
Let
. There exist
such that
. Now
By definition of
, each
, for some
. Therefore,
However, is a soft semi-algebra, which implies that . This proves that . Hence, is a soft algebra. □
Theorem 3. Let be a soft semi-algebra on X and let be the soft algebra generated by . Then, if , for some .
Proof. From Proposition 1, and, by Theorem 2, , since is a soft algebra.
The converse is clear, since , for , and is a soft algebra, so . □
Proposition 2. Let and let Σ be a soft algebra on X. Thenis a soft algebra on and is denoted by or simply . Proof. Since
and
, so
. If
, then
for some
. Since
, we have
. Thus,
. Suppose that
. Then for each
, there exists
such that
. Since
, so
This implies that . □
Theorem 4. Let be a subcollection of and let . Thenwhere . Proof. Let
. Then
for some
. Therefore,
and, hence,
. Since by Proposition 2,
is a soft algebra on
Y. Thus, Lemma 2 guarantees that
. To prove the other way of the inclusion, we first need to check that
is a soft algebra. Evidently,
because
. Suppose that
. Then
. Since
, this means that
. Assume that
. Then
. Therefore,
Hence,
. This proves that
is a soft algebra on
X. Suppose that
. Then
, and so,
. Thus,
and, by Lemma 2,
. Now, if
, then
for some
and, hence,
. This concludes that
. Thus,
. □
Lemma 3. Let be a soft mapping. Then
- 1.
if Σ is a soft algebra on X, then is a soft algebra on Y.
- 2.
If is a soft algebra on Y, the set is a soft algebra on X.
Proof. Both (1) and (2) follow from the fact that
for each soft set
over
Y, and
for each collection
of soft sets over
Y (see Theorem 14 in [
31]). □
We shall remark that the direct image of a soft algebra under a soft mapping need not be a soft algebra.
Example 6. Let , , and . Define the mapping by and , for all . Let , where and . The image of the soft algebra Σ is , where , which is not a soft algebra on Y.
Theorem 5. Let be a soft mapping. Thenfor each collection of soft sets over Y. Proof. By Lemma 3 (2), is a soft algebra and , and this implies that . However, by Lemma 3 (1), the set is a soft algebra, and it contains , hence . Therefore, . This shows that . □
4. Ordinary and Soft Algebras
Proposition 3. Let Σ be a soft algebra on X, parameterized by . Then is an ordinary algebra on X for each .
Proof. Since , then for each . Let . Then and, since is a soft algebra, so . However, and so, . Let be a family of sets in . Then, for each n, , and thus, . Hence, . □
The converse of this lemma is not always true, particularly when
, and the counterexample can be concluded from Example 5 in [
34]. The scenario is different when
.
Theorem 6. Let and let be a family of subsets of X. Then is a soft algebra if is an ordinary algebra on X.
Proof. The first direction follows from Proposition 3.
Conversely, suppose
is an algebra. Clearly,
, and so,
. Let
. Then,
and
. Since
is an algebra, so
. Therefore,
. Let
be a collection of soft sets in
. This implies that
for each
, and thus,
, as
is an algebra on
X. Therefore,
This proves that is a soft algebra on X. □
Theorem 7. Let be an (ordinary) algebra on X and be a set of parameters. Then
- (1)
the family of soft sets forms a soft algebra on X, where .
- (2)
The family of soft sets forms a soft algebra on X, where .
Proof. The proof is quite comparable to the second part of the proof for the preceding result. □
Remark 2. The above formula holds true for any family of subsets of a given universe. Namely, we generate a collection of soft sets from an ordinary family of sets.
The soft algebra is called a soft algebra on X generated by , and the soft algebra is called an extended soft algebra on X via .
Observe that for each .
The following examples show how the process in Theorem 7 can be used:
Example 7. Let and . Consider the following ordinary algebra on X: . Applying the first formula, we conclude the following soft algebra on X:
where
Applying the second formula, we conclude the following soft algebra on X:
A less trivial example is
Example 8. Let be the finite–cofinite algebra on X. That is, If X is finite, . The soft algebra on X generated by is given by the following family: When we need to define the finite–cofinite algebra on X in soft settings, we normally do so as in Example 3, i.e., However, both are equivalent. This example demonstrates how effectively our formulas produce soft algebras. We shall call the finite–cofinite soft algebra on X.
It is worth noting that the general formula for constructing soft algebras provided by Theorem 7 can be improved by the use of several ordinary algebras.
Corollary 1. Let be a collection of (ordinary) algebras on X indexed by a set of parameters . The family of all soft sets forms a soft algebra on X, where .
Notice that, if for each , , then .
We have seen that each soft algebra produces a family of (ordinary) algebras of size , so we obtain the following observation:
Lemma 4. Let be the family of all ordinary algebras on X from a soft algebra Σ. Then Proof. It can be concluded from the definition of soft sets and the soft algebra generated by . □
Theorem 8. Let be a family of ordinary algebras on X indexed by . Then Proof. Let
. Then
Hence, The converse can be followed by reversing the above steps. □
Consequently, we have the following corollary:
Corollary 2. Let be a subcollection of , such that . Thenwhere is the family of all soft sets , such that for each .