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Article

Fuzzy Filters of Hoops Based on Fuzzy Points

by
Mona Aaly Kologani
1,
Mohammad Mohseni Takallo
2 and
Hee Sik Kim
3,*
1
Hatef Higher Education Institute, Zahedan 8301, Iran
2
Department of Mathematics, Shahid Beheshti University, Tehran 7561, Iran
3
Department of Mathematics, Research Institute of Natural Sciences, Hanyang University, Seoul 04763, Korea
*
Author to whom correspondence should be addressed.
Mathematics 2019, 7(5), 430; https://doi.org/10.3390/math7050430
Submission received: 12 April 2019 / Revised: 28 April 2019 / Accepted: 6 May 2019 / Published: 14 May 2019
(This article belongs to the Section Mathematics and Computer Science)

Abstract

:
In this paper, we define the concepts of ( , ) and ( , q ) -fuzzy filters of hoops, discuss some properties, and find some equivalent definitions of them. We define a congruence relation on hoops by an ( , ) -fuzzy filter and show that the quotient structure of this relation is a hoop.

1. Introduction

The hoop, which was introduced by Bosbach in [1,2], is naturally-ordered commutative residuated integral monoids. Several properties of hoops are displayed in [3,4,5,6,7,8,9,10,11,12,13,14]. The idea of the quasi-coincidence of a fuzzy point with a fuzzy set, which was introduced in [15], has played a very important role in generating fuzzy subalgebras of B C K / B C I -algebras, called ( α , β ) -fuzzy subalgebras of B C K / B C I -algebras, introduced by Jun [16]. Moreover, ( , q ) -fuzzy subalgebra is a useful generalization of a fuzzy subalgebra in B C K / B C I -algebras. Many researcher applied the fuzzy structures on logical algebras [17,18,19,20,21,22]. Now, in this paper, we want to introduce these notions and investigate the existing fuzzy subsystems on hoops. Borzooei and Aaly Kologani in [8] defined the concepts of filters, (positive) implicative and fantastic filters of the hoop, and discussed their properties. Then, they defined a congruence relation on the hoop by a filter and proved that the quotient structure of this relation is a hoop. Finally, they investigated under what conditions that quotient structure will be the Brouwerian semilattice, Heyting algebra, and the Wajsberg hoop.
The aim of the paper is to define the concepts of ( , ) -fuzzy filters and ( , q ) -fuzzy filters of hoops, discuss some properties and find equivalent definitions of them. By using an ( , ) -fuzzy filter of hoops, we define a congruence relation on hoops, and we show that the quotient structure of this relation forms a hoop.

2. Preliminaries

By a hoop, we mean an algebraic structure ( H , , , 1 ) in which ( H , , 1 ) is a commutative, monoid and for any x , y , z H , the following assertions are valid.
(H1)
x x = 1 .
(H2)
x ( x y ) = y ( y x ) .
(H3)
x ( y z ) = ( x y ) z (See [1,2]).
For any x , y H , we can define a relation ≤ on hoop H by x y if and only if x y = 1 . It is easy to see that ( H , ) is a poset. Therefore, in any hoop H, if for any x H , there exists an element 0 H such that 0 x , then H is called a bounded hoop. Let x 0 = 1 , x n = x n - 1 x , for any n N . If H is a bounded hoop, then we define a negation “ ′ ” on H by x = x 0 , for all x H . By a sub-hoop of a hoop H, we mean a subset S of H that satisfies the condition:
( x , y H ) ( x , y S x y S , x y S ) .
Note that every non-empty sub-hoop contains the element 1.
Proposition 1.
[23] Let ( H , , , 1 ) be a hoop. Then, the following conditions hold, for all x , y , z H :
  • ( i ) ( H , ) is a meet-semilattice such that x y = x ( x y ) .
  • ( i i ) x y z if and only if x y z .
  • ( i i i ) x y x , y and x n x , for any n N .
  • ( i v ) x y x .
  • ( v ) 1 x = x and x 1 = 1 .
  • ( v i ) x ( x y ) y .
  • ( v i i ) ( x y ) ( y z ) ( x z ) .
  • ( v i i i ) x y implies x z y z , z x z y and y z x z .
Let F be a non-empty subset of a hoop H. Then, F is called a filter of H if, for any x , y F , x y F and, for any y H and x F , if x y , then y F (see [23]).
Let X be a nonempty set, x X and t ( 0 , 1 ] . The fuzzy point with support x and value t is defined as:
μ ( y ) : = t ( 0 , 1 ] if y = x , 0 if y x ,
and is denoted by x t .
For a fuzzy point x t and a fuzzy set λ in a set X, Pu and Liu [15] defined the symbol x t α λ , where α { , q , q , q } . This means that, x t λ (resp. x t q λ ) if λ ( x ) t (resp. λ ( x ) + t > 1 ). Then, x t is said to belong to (resp. be quasi-coincident with) a fuzzy set λ . Moreover, x t q λ (resp. x t q λ ) means that x t λ or x t q λ (resp. x t λ and x t q λ ).
From now one, we let H denote a hoop, unless otherwise specified.

3. ( α , β ) -Fuzzy Filters for ( α , β ) { ( , ) , ( , q ) }

In this section, we define ( α , β ) -fuzzy filters of hoops for ( α , β ) { ( , ) , ( , q ) } , and we investigate some of their properties. Furthermore, we define a congruence relation on hoops by these filters and prove that the corresponding quotients are a bounded hoop.
Definition 1.
Let ( α , β ) { ( , ) , ( , q ) } . Let λ be a fuzzy set of H. Then, λ is called an ( α , β ) -fuzzy filter of H if the following assertions are valid.
( x H ) ( t ( 0 , 1 ] ) ( x t α λ 1 t β λ ) ,
( x , y H ) ( t , k ( 0 , 1 ] ) ( x t α λ , ( x y ) k α λ y min { t , k } β λ ) .
Example 1.
On the set H = { 0 , a , b , 1 } , we define two operations and → on H by:
Mathematics 07 00430 i001
Then, (H, , →, 1) is a hoop. Define the fuzzy set λ in H by λ ( 0 ) = λ ( a ) = 0.4 , λ ( b ) = 0.6 , and λ ( 1 ) = 0.8 . Then, λ is an ( , ) -fuzzy filter of H, and it is clear that λ is an ( , q ) -fuzzy filter of H.
Theorem 1.
A fuzzy set λ in H is an ( , ) -fuzzy filter of H if and only if the following conditions hold:
( x H ) ( λ ( 1 ) λ ( x ) ) ,
( x , y H ) ( λ ( y ) min { λ ( x ) , λ ( x y ) } ) .
Proof. 
Let λ be an ( , ) -fuzzy filter of H and x H such that λ ( x ) = t . Since λ is an ( , ) -fuzzy filter of H, by Definition 1, λ ( 1 ) t = λ ( x ) . Therefore, λ ( 1 ) λ ( x ) . Now, let x , y H . If λ ( x ) = t and λ ( x y ) = k , then x t λ and ( x y ) k λ . Since λ is an ( , ) -fuzzy filter of H, we have y min { t , k } λ , so:
λ ( y ) min { t , k } = min { λ ( x ) , λ ( x y ) }
Conversely, suppose x H and t ( 0 , 1 ] . If x t λ , then λ ( x ) t . Since λ ( 1 ) λ ( x ) , we have λ ( 1 ) t , and so, 1 t λ . Furthermore, if x t λ and ( x y ) k λ , then by assumption,
λ ( y ) min { λ ( x ) , λ ( x y ) } min { t , k }
Hence, y min { t , k } λ . Therefore, λ is an ( , ) -fuzzy filter of H. □
Proposition 2.
If λ is an ( , ) -fuzzy filter of H, then the following statement holds.
( x , y H ) ( x y λ ( x ) λ ( y ) ) .
Proof. 
Let x , y H such that x y . Therefore, it is clear that x y = 1 . Since λ is an ( , ) -fuzzy filter of H, by Theorem 1, λ ( 1 ) λ ( x ) and λ ( y ) min { λ ( x ) , λ ( x y ) } , for any x , y H . Then:
λ ( y ) min { λ ( x ) , λ ( x y ) } = m i n { λ ( x ) , λ ( 1 ) } = λ ( x )
Hence, λ ( y ) λ ( x ) . □
Theorem 2.
A fuzzy set λ in H is an ( , ) -fuzzy sub-hoop of H such that, for any x H , λ ( x ) λ ( 1 ) . Then, for any x , y , z H , the following statements are equivalent:
  • ( i ) λ is an ( , ) -fuzzy filter of H,
  • ( i i ) if ( x y ) t λ and ( y z ) k λ , then ( x z ) min { t , k } λ ,
  • ( i i i ) if ( x y ) t λ and ( x z ) k λ , then ( y z ) min { t , k } λ .
Proof. 
( i ) ( i i ) Let λ be an ( , ) -fuzzy filter of H such that ( x y ) t λ and ( y z ) k λ . Then, λ ( x y ) t and λ ( y z ) k . By Proposition 1(vii), x y ( y z ) ( x z ) . Then, by Proposition 2,
λ ( x y ) λ ( ( y z ) ( x z ) )
Since ( x y ) t λ , we have ( ( y z ) ( x z ) ) t λ . Thus, by (i),
min { t , k } min { λ ( x y ) , λ ( y z ) } min { λ ( ( y z ) ( x z ) ) , λ ( y z ) } λ ( x z )
Hence, ( x z ) min { t , k } λ .
  • ( i i ) ( i ) It is enough to let x = 1 .
  • ( i ) ( i i i ) Let λ be an ( , ) -fuzzy filter of H such that ( x y ) t λ and ( x z ) k λ . Then, by Proposition 1(vi), z x ( x y ) z y . Thus, x y ( z x ) ( z y ) . By Proposition 2, λ ( x y ) λ ( ( z x ) ( z y ) ) , so:
    min { t , k } min { λ ( x y ) , λ ( z x ) } min { λ ( z x ) , λ ( ( z x ) ( z y ) ) } λ ( z y )
    Hence, ( y z ) min { t , k } λ .
  • ( i i i ) ( i ) It is enough to let z = 1 . □
Theorem 3.
Let λ be an ( , ) -fuzzy filter of H, x , y H , and t ( 0 , 1 ] . Define:
x λ y i f a n d o n l y i f ( x y ) t λ a n d ( y x ) t λ
Then, λ is a congruence relation on H.
Proof. 
It is clear that λ is reflexive and symmetric. Now, we prove that λ is transitive. For this, suppose x λ y and y λ z . Then, there exists t , m ( 0 , 1 ] such that ( x y ) t λ and ( y x ) t λ , and also, ( y z ) m λ and ( z y ) m λ . By Proposition 1(vii), x y ( y z ) ( x z ) , and by Proposition 2, we have:
min { t , m } min { λ ( x y ) , λ ( y z ) } min { λ ( y z ) , λ ( ( y z ) ( x z ) ) } λ ( x z )
Hence, ( x z ) min { t , m } λ . In a similar way, we get that:
min { t , m } min { λ ( z y ) , λ ( y x ) } min { λ ( y x ) , λ ( ( y x ) ( z x ) ) } λ ( z x )
Hence, ( z x ) min { t , m } λ . Therefore, x λ z . Suppose that x λ y . We show that x z λ y z , for any x , y , z H . Since x λ y , for any t ( 0 , 1 ] , we have ( x y ) t λ and ( y x ) t λ . Since y z y z , y z ( y z ) . By Proposition 1(viii), x y x ( z ( y z ) ) , and so, x y ( x z ) ( y z ) . Since λ is an ( , ) -fuzzy filter of H, by Proposition 2, we have:
t λ ( x y ) λ ( ( x z ) ( y z ) )
Hence, ( ( x z ) ( y z ) ) t λ . In a similar way, since x z x z , we get x z ( x z ) . By Proposition 1(viii), y x y ( z ( x z ) ) , and so, y x ( y z ) ( y z ) . Since λ is an ( , ) -fuzzy filter of H, by Proposition 2, we have:
t λ ( y x ) λ ( ( y z ) ( x z ) )
Hence, ( ( y z ) ( x z ) ) t λ . Therefore, x z λ y z . Finally, suppose that x λ y ; we show that x z λ y z , for any x , y , z H . Since x λ y , for any t ( 0 , 1 ] , we have ( x y ) t λ and ( y x ) t λ . By Proposition 1(vii) and Proposition 2,
t λ ( x y ) λ ( ( y z ) ( x z ) )
and:
t λ ( y x ) λ ( ( x z ) ( y z ) )
Hence, x z λ y z . It is easy to see that z x λ z y . Therefore, λ is a congruence relation on H. □
Theorem 4.
Let H λ = { [ a ] λ a H } , and operations and on H λ are defined as follows:
[ a ] λ [ b ] λ = [ a b ] λ and [ a ] λ [ b ] λ = [ a b ] λ
Then, ( H λ , , , [ 1 ] λ ) is a hoop.
Proof. 
We have [ a ] λ = [ b ] λ and [ c ] λ = [ d ] λ if and only if a λ b and c λ d . Since λ is the congruence relation on H, then all above operations are well-defined. Thus, by routine calculation, we can see that H λ is a hoop. □
Now, we define a relation on H λ by:
[ a ] λ [ b ] λ if and only if ( a b ) t λ , for any a , b H and t ( 0 , 1 ]
It is easy to see that ( H λ , ) is a poset.
Note: According to the definition of the congruence relation, it is clear that:
[ 1 ] λ = { a H ( a 1 ) t λ and ( 1 a ) t λ } = { a H a t λ } .
Therefore, as we define a relation on quotient, [ a ] λ [ b ] λ if and only if ( a b ) t λ , it is similar to writing [ a ] λ [ b ] λ if and only if [ a ] λ [ b ] λ [ 1 ] λ .
Theorem 5.
If λ is a non-zero ( , ) -fuzzy filter of H, then the set:
H 0 : = { x H λ ( x ) 0 }
is a filter of H.
Proof. 
Let x H 0 . Since λ ( x ) 0 , we conclude that there exists t ( 0 , 1 ] such that λ ( x ) t . Moreover, from λ being an ( , ) -fuzzy filter of H, by Definition 1, x t λ , then 1 t λ . Hence, λ ( 1 ) λ ( x ) = t 0 , and so, 1 H 0 . Now, suppose that x , x y H 0 . Then, there exist t , k ( 0 , 1 ] , such that λ ( x ) t and λ ( x y ) k , and so, x t λ and ( x y ) k λ . Thus, by Definition 1, y min { t , k } λ , and so, λ ( y ) min { t , k } 0 . Hence, y H 0 . Therefore, H 0 is a filter of H. □
Proposition 3.
If λ is a non-zero ( , q ) -fuzzy filter of H, then λ ( 1 ) > 0 .
Proof. 
Let λ ( 1 ) = 0 . Since λ is an ( , q ) -fuzzy filter of H, by Theorem 1, for any x H , λ ( x ) λ ( 1 ) = 0 . Hence, for any x H , λ ( x ) = 0 , and so, λ is a zero ( , q ) -fuzzy filter of H, which is a contradiction. Therefore, λ ( 1 ) > 0 . □
Theorem 6.
For any filter F of H and t ( 0 , 0.5 ] , there exists an ( , q ) -fuzzy filter λ of H such that its ∈-level set is equal to F.
Proof. 
Let t ( 0 , 0.5 ] and λ : H [ 0 , 1 ] be defined by λ ( x ) = t , for any x F , and λ ( x ) = 0 , otherwise. By this definition, it is clear that U ( λ ; t ) = F . Therefore, it is enough to prove that λ is an ( , q ) -fuzzy filter of H. Let x H . Then, λ ( x ) = 0 or λ ( x ) = t . Since F is a filter of H and 1 F , we have t = λ ( 1 ) λ ( x ) , for any x H . Now, suppose that x t λ and ( x y ) k λ . We consider the following cases:
  • Case 1: If λ ( x ) = t and λ ( x y ) = t , then x , x y F . Since F is a filter of H, we have y F , and so, λ ( y ) min { λ ( x ) , λ ( x y ) } = t . Hence, y t λ . Therefore, λ is an ( , q ) -fuzzy filter of H.
  • Case 2: If λ ( x ) = t and λ ( x y ) = 0 , then it is clear that:
    λ ( y ) min { λ ( x ) , λ ( x y ) } = 0
    Hence, y 0 λ . Therefore, λ is an ( , q ) -fuzzy filter of H.
  • Case 3: If λ ( x ) = 0 and λ ( x y ) = 0 , then it is clear that:
    λ ( y ) min { λ ( x ) , λ ( x y ) } = 0
    Hence, y 0 λ . Therefore, λ is an ( , q ) -fuzzy filter of H.
Therefore, in all cases, λ is an ( , q ) -fuzzy filter of H and U ( λ ; t ) = F . □
For any fuzzy set λ in H and t ( 0 , 1 ] , we define three sets that are called the ∈-level set, q-set, and q -set, respectively, as follows.
U ( λ ; t ) : = { x H λ ( x ) t } . λ q t : = { x H x t q λ } . λ q t : = { x H x t q λ } .
Theorem 7.
Given a fuzzy set λ in H, the following statements are equivalent.
(i)
The nonempty ∈-level set U ( λ ; t ) of λ is a filter of H, for all t ( 0.5 , 1 ] .
(ii)
λ satisfies the following assertions.
( x H ) ( λ ( x ) max { λ ( 1 ) , 0.5 } ) .
( x , y H ) ( max { λ ( y ) , 0.5 } min { λ ( x y ) , λ ( x ) } ) .
Proof. 
Let x H and t ( 0.5 , 1 ] such that λ ( x ) = t . Then, x U ( λ ; t ) . Since U ( λ ; t ) is a filter of H, 1 U ( λ ; t ) . Thus, λ ( 1 ) t . Moreover, since t ( 0.5 , 1 ] , we have max { λ ( 1 ) , 0.5 } λ ( 1 ) t = λ ( x ) . Hence, max { λ ( 1 ) , 0.5 } λ ( x ) . Now, suppose x , y H and t , k ( 0.5 , 1 ] such that λ ( x ) = t and λ ( x y ) = k . Then, x , x y U ( λ ; min { t , k } ) . Since U ( λ ; min { t , k } ) is a filter of H, we have y U ( λ ; min { t , k } ) . Thus, λ ( y ) min { t , k } . From t , k ( 0.5 , 1 ] , we conclude that,
max { λ ( y ) , 0.5 } min { t , k } = min { λ ( x ) , λ ( x y ) }
Hence,
max { λ ( y ) , 0.5 } min { λ ( x ) , λ ( x y ) }
Conversely, let x U ( λ ; t ) . Then, λ ( x ) t . Since t ( 0.5 , 1 ] , by assumption:
t λ ( x ) max { λ ( 1 ) , 0.5 } = λ ( 1 )
Thus, λ ( 1 ) t , so 1 U ( λ ; t ) . Now, suppose that x , x y U ( λ ; t ) , for any x , y H and t ( 0.5 , 1 ] . Then, λ ( x ) t and λ ( x y ) t . By assumption,
max { λ ( y ) , 0.5 } min { λ ( x y ) , λ ( x ) } t
Since t ( 0.5 , 1 ] , we have λ ( y ) t , so y U ( λ ; t ) . Hence, U ( λ ; t ) is a filter of H. □
It is clear that every ( , ) -fuzzy filter of H is an ( , q ) -fuzzy filter of H. However, the converse may not be true, in general.
Example 2.
On the set H = { 0 , a , b , c , d , 1 } , we define two operations and → as follows:
Mathematics 07 00430 i002
By routine calculations, it is clear that ( H , , , 0 , 1 ) is a bounded hoop. Define a fuzzy set λ in H as follows:
λ : H [ 0 , 1 ] , x 0.1 if x = 0 , 0.1 if x = a , 0.2 if x = b , 0.3 if x = c , 0.1 if x = d , 0.5 if x = 1
It is easy to see that λ is an ( , q ) -fuzzy filter of hoop H, but it is not an ( , q ) -fuzzy filter of H; because:
0.2 = λ ( b ) min { λ ( c ) , λ ( c b ) } = min { λ ( c ) , λ ( 1 ) } = min { 0.3 , 0.5 } = 0.3
However, it is not an ( , ) -fuzzy filter of H.
Now, we investigate under which conditions any ( , q ) -fuzzy filter is an ( , ) -fuzzy filter.
Theorem 8.
If an ( , q ) -fuzzy filter λ of H satisfies the condition:
( x H ) ( λ ( x ) < 0.5 ) ,
then λ is an ( , ) -fuzzy filter of H.
Proof. 
Let x t λ , for any x H and t ( 0 , 0.5 ) . Since λ is an ( , q ) -fuzzy filter of H, by Definition 1, 1 t λ or 1 t q λ . If 1 t λ , then the proof is clear. If 1 t q λ , then λ ( 1 ) + t > 1 . Since t ( 0 , 0.5 ) , 1 - t [ 0.5 , 1 ] , then λ ( 1 ) > t . Hence, 1 t λ . Now, suppose that x t λ and ( x y ) k λ . From λ is an ( , q ) -fuzzy filter of H, by Definition 1, y min { t , k } λ or y min { t , k } q λ . If y min { t , k } λ , then the proof is complete. However, if y min { t , k } q λ , then λ ( y ) + min { t , k } > 1 , and so, λ ( y ) > 1 - min { t , k } . Since t ( 0 , 0.5 ) , we have 1 - min { t , k } [ 0.5 , 1 ] , and so, λ ( y ) > min { t , k } . Then, y min { t , k } λ . Therefore, λ is an ( , ) -fuzzy filter of H. □
Theorem 9.
If λ is an ( , q ) -fuzzy filter of H, then the q-set λ q t is a filter of H, for all t ( 0.5 , 1 ] .
Proof. 
Let x λ q t , for any x H and t ( 0.5 , 1 ] . Then, λ ( x ) + t > 1 , and so, λ ( x ) > 1 - t . Since λ is an ( , q ) -fuzzy filter of H, by Definition 1, we have 1 1 - t λ or 1 1 - t q λ . If 1 1 - t q λ , then it is clear that λ ( 1 ) > t . Since t ( 0.5 , 1 ] , we have λ ( 1 ) + t > 2 t > 1 , and so, 1 λ q t . If 1 1 - t λ , then λ ( 1 ) 1 - t , and so, λ ( 1 ) + t > 1 . Thus, in both cases, 1 λ q t . Now, suppose that x , x y λ q t , for any x , y H and t ( 0.5 , 1 ] . Then, λ ( x ) + t > 1 and λ ( x y ) + t > 1 , and so, λ ( x ) > 1 - t and λ ( x y ) > 1 - t . Since λ is an ( , q ) -fuzzy filter of H, by Definition 1, we have y min { 1 - t , 1 - t } λ or y min { 1 - t , 1 - t } q λ . If y 1 - t λ , then λ ( y ) > 1 - t , and so, λ ( y ) + t > 1 . If y 1 - t q λ , then λ ( y ) + 1 - t > 1 , and so, λ ( y ) > t . Since t ( 0.5 , 1 ] , we have λ ( y ) + t > 2 t > 1 . Hence, in both cases, y λ q t . Therefore, λ q t is a filter of H, for any t ( 0.5 , 1 ] . □
Theorem 10.
A fuzzy set λ in H is an ( , q ) -fuzzy filter of H if and only if the following assertion is valid.
( x , y H ) λ ( 1 ) min { λ ( x ) , 0.5 } λ ( y ) min { λ ( x ) , λ ( x y ) , 0.5 } .
Proof. 
Let x t λ , for any x H and t ( 0 , 1 ] . Since λ is an ( , q ) -fuzzy filter of H, we have 1 t λ or 1 t q λ . It means that λ ( 1 ) t or λ ( 1 ) > 1 - t . Therefore, λ ( 1 ) min { λ ( x ) , 0.5 } . In a similar way, if x t λ and ( x y ) k λ , for any x , y H and t , k ( 0 , 1 ] , since λ is an ( , q ) -fuzzy filter of H, then we have y min { t , k } λ or y min { t , k } q λ . This means that λ ( y ) min { t , k } or λ ( 1 ) > min { 1 - t , 1 - k } . Therefore, λ ( y ) min { λ ( x ) , λ ( x y ) , 0.5 } . Conversely, let x t λ , for any t ( 0 , 1 ] and x H . Then, by assumption, we have λ ( 1 ) min { λ ( x ) , 0.5 } . If t ( 0 , 0.5 ] , then λ ( 1 ) λ ( x ) = t , and so, 1 t λ . If t ( 0.5 , 1 ] , then λ ( 1 ) 0.5 , and so, λ ( 1 ) + t > t + 0.5 > 1 ; thus, 1 t q λ . Hence, 1 t q λ . Now, suppose that x t λ and ( x y ) k λ , for any x , y H and t , k ( 0 , 1 ] . Then, by assumption, we have λ ( y ) min { λ ( x ) , λ ( x y ) , 0.5 } . If t , k ( 0 , 0.5 ] , then:
λ ( y ) min { λ ( x ) , λ ( x y ) , 0.5 } = min { t , k }
Hence, y min { t , k } λ . If t , k ( 0.5 , 1 ] , then:
λ ( y ) min { λ ( x ) , λ ( x y ) , 0.5 } = 0.5
Therefore, λ ( y ) + min { t , k } > min { t , k } + 0.5 > 1 . Thus, y min { t , k } q λ . Hence, y min { t , k } q λ . Therefore, λ is an ( , q ) -fuzzy filter of H. □
Theorem 11.
A fuzzy set λ in H is an ( , q ) -fuzzy filter of H if and only if the non-empty ∈-level set U ( λ ; t ) of λ is a filter of H, for all t ( 0 , 0.5 ] .
Proof. 
Let λ be an ( , q ) -fuzzy filter of H and x U ( λ ; t ) , for any t ( 0 , 0.5 ] . Then, λ ( x ) t , and so, x t λ . Since λ is an ( , q ) -fuzzy filter of H, 1 t λ or 1 t q λ . If 1 t λ , then it is clear that 1 U ( λ ; t ) , and if 1 t q λ , then λ ( 1 ) > 1 - t . Since t ( 0 , 0.5 ] , 1 - t ( 0.5 , 1 ] , so λ ( 1 ) > 1 - t > t . Thus, 1 U ( λ ; t ) . Now, suppose that x , x y U ( λ ; t ) , then λ ( x ) t and λ ( x y ) t , and so, x t λ and ( x y ) t λ . Since λ is an ( , q ) -fuzzy filter of H, y t λ or y t q λ . If y t λ , then it is clear that y U ( λ ; t ) , and if y t q λ , then λ ( y ) > 1 - t . Since t ( 0 , 0.5 ] , 1 - t ( 0.5 , 1 ] , so λ ( y ) > 1 - t > t . Thus, y U ( λ ; t ) . Therefore, U ( λ ; t ) is a filter of H, for any t ( 0 , 0.5 ] .
Conversely, suppose U ( λ ; t ) is a filter of H and x t λ , for any x H and t ( 0 , 0.5 ] . Then, λ ( x ) t , so x U ( λ ; t ) . Since U ( λ ; t ) is a filter of H, 1 U ( λ ; t ) , so λ ( 1 ) t . Hence, 1 t λ , and so, 1 t q λ . Now, let x t λ and ( x y ) k λ , for any x , y H and t , k ( 0 , 0.5 ] . Then, λ ( x ) t and λ ( x y ) k , and so, x , x y U ( λ ; min { t , k } ) . Since U ( λ ; t ) is a filter of H, y U ( λ ; min { t , k } ) , and so, λ ( y ) min { t , k } . Hence, y min { t , k } λ . Therefore, y min { t , k } q λ . Therefore, λ is an ( , q ) -fuzzy filter of H, for any t ( 0 , 0.5 ] . □
Theorem 12.
A fuzzy set λ in H is an ( , q ) -fuzzy filter of H if and only if the following assertion is valid.
( x , y H ) λ ( x y ) min { λ ( x ) , λ ( y ) , 0.5 } x y λ ( y ) min { λ ( x ) , 0.5 } .
Proof. 
Assume that λ is an ( , q ) -fuzzy filter of H and x , y H . Then, by Theorem 11, U ( λ ; t ) is a filter of H, for any t ( 0 , 0.5 ] . If x , y U ( λ ; t ) and t ( 0 , 0.5 ] , then x y U ( λ ; t ) . Thus, λ ( x y ) t = min { λ ( x ) , λ ( y ) } . If t ( 0.5 , 1 ] , it is clear that λ ( x y ) min { λ ( x ) , λ ( y ) , 0.5 } . Now, suppose x y . If λ ( x ) t and t ( 0 , 0.5 ] , then x U ( λ ; t ) . Since U ( λ ; t ) is a filter of H, y U ( λ ; t ) . Thus, λ ( y ) λ ( x ) , for t ( 0 , 0.5 ] . If t ( 0.5 , 1 ] , then λ ( y ) min { λ ( x ) , 0.5 } .
Conversely, let λ be a fuzzy set in H that satisfies the condition (12). Since x 1 for all x H , we have λ ( 1 ) min { λ ( x ) , 0.5 } for all x H . Since x ( x y ) y for all x , y H , we get:
λ ( y ) min { λ ( x ( x y ) ) , 0.5 } min { min { λ ( x ) , λ ( x y ) , 0.5 } , 0.5 } = min { λ ( x ) , λ ( x y ) , 0.5 }
for all x , y H . It follows from Theorem 10 that λ is an ( , q ) -fuzzy filter of H. □
Theorem 13.
A fuzzy set λ in H is an ( , q ) -fuzzy filter of H if and only if λ q t is a filter of H, for all t ( 0 , 1 ] (we call λ q t an q -level filter of λ).
Proof. 
Let λ be an ( , q ) -fuzzy filter of H and x λ q t , for any x H and t ( 0 , 1 ] . Then, x U ( λ ; t ) or x λ q t . This means that x t λ or x 1 - t λ . Since λ is an ( , q ) -fuzzy filter of H, we have, if x t λ , then 1 t λ or 1 t q λ . Furthermore, if x 1 - t λ , then 1 1 - t λ or x 1 - t q λ ; this means that x t q λ or x t λ . Hence, in both cases, 1 t q λ , and so, 1 λ q t . In a similar way, let x , x y λ q t , for x , y H and t ( 0 , 1 ] . Then, x , x y U ( λ ; t ) or x , x y λ q t or x U ( λ ; t ) and x y λ q t . Therefore, we have the following cases:
  • Case 1: if x , x y U ( λ ; t ) , then x t λ and ( x y ) t λ . Since λ is an ( , q ) -fuzzy filter of H, y t λ or y t q λ . Therefore, y λ q t .
  • Case 2: if x , x y λ q t , then x 1 - t λ and ( x y ) 1 - t λ . Since λ is an ( , q ) -fuzzy filter of H, y 1 - t λ or y 1 - t q λ . It is equivalent to y t q λ or y t λ , respectively. Therefore, y λ q t .
  • Case 3: if x U ( λ ; t ) and x y λ q t , then x t λ and ( x y ) 1 - t λ . Since λ is an ( , q ) -fuzzy filter of H, λ ( y ) min { 1 - t , t } , and so, it is equal to y t λ or y t q λ . Thus, in both cases, y λ q t .
Therefore, λ q t is a filter of H.
Conversely, let x t λ , for any x H and t ( 0 , 1 ] . Since λ q t is a filter of H, 1 λ q t . Then, 1 t q λ . Now, suppose that x t λ and ( x y ) k λ , for any x , y H and t , k ( 0 , 1 ] . Then, it is clear that x , x y λ q min { t , k } . Since λ q t is a filter of H, y λ q min { t , k } . Therefore, y min { t , k } λ or y min { t , k } q λ . Hence, y min { t , k } q λ . Therefore, λ is an ( , q ) -fuzzy filter of H. □
Theorem 14.
Let f : H K be a homomorphism of hoops. If λ and μ are ( , q ) -fuzzy filters of H and K, respectively, then:
(i)
f - 1 ( μ ) is an ( , q ) -fuzzy filter of H.
(ii)
If f is onto and λ satisfies the condition:
( T H ) ( x 0 T ) λ ( x 0 ) = sup x T λ ( x ) ,
then f ( λ ) is an ( , q ) -fuzzy filter of K.
Proof. 
( i ) Let x t f - 1 ( μ ) , for any x H and t ( 0 , 1 ] . Then, f ( x ) t μ . Since μ is an ( , q ) -fuzzy filter of H, we have f ( 1 ) t q μ . Thus, 1 t q f - 1 ( μ ) . Now, suppose x t f - 1 ( μ ) and ( x y ) k f - 1 ( μ ) , for any x , y H and t , k ( 0 , 1 ] . Then, f ( x ) t μ and f ( x y ) k μ . Since μ is an ( , q ) -fuzzy filter of H, we have f ( y ) min { t , k } q μ . Hence, y min { t , k } q f - 1 ( μ ) . Therefore, f - 1 ( μ ) is an ( , q ) -fuzzy filter of H.
( i i ) Let a K and t ( 0 , 1 ] be such that a t f ( λ ) . Then, ( f ( λ ) ) ( a ) t . By assumption, there exists x f - 1 ( a ) such that λ ( x ) = s u p z f - 1 ( a ) λ ( z ) . Then, x t λ . Since λ is an ( , q ) -fuzzy filter of H, we have 1 t λ . Now, 1 f - 1 ( 1 ) , so ( f ( λ ) ) ( 1 ) λ ( 1 ) , then ( f ( λ ) ) ( 1 ) t or ( f ( λ ) ) ( 1 ) + t > 1 . Thus, 1 t q f ( λ ) . In a similar way, let a , a b K and t , k ( 0 , 1 ] be such that a t f ( λ ) and ( a b ) k f ( λ ) . Then, ( f ( λ ) ) ( a ) t and ( f ( λ ) ) ( a b ) k . By assumption, there exist x f - 1 ( a ) and x y f - 1 ( a b ) such that λ ( x ) = s u p z f - 1 ( a ) λ ( z ) and λ ( x y ) = s u p w f - 1 ( a b ) λ ( w ) . Then, x t λ and ( x y ) k λ . Since λ is an ( , q ) -fuzzy filter of H, we have y min { t , k } λ . Now, y f - 1 ( y ) , so ( f ( λ ) ) ( y ) λ ( y ) , then ( f ( λ ) ) ( y ) min { t , k } or ( f ( λ ) ) ( y ) + min { t , k } > 1 . Thus, y min { t , k } q f ( λ ) . □
Theorem 15.
Let λ be an ( , q ) -fuzzy filter of H such that:
| { λ ( x ) λ ( x ) < 0.5 } | 2 .
Then, there exist two ( , q ) -fuzzy filters μ and ν of H such that:
(i)
λ = μ ν .
(ii)
Im ( μ ) and Im ( ν ) have at least two elements.
(iii)
μ and ν do not have the same family of q -level filters.
Proof. 
Let { λ ( x ) λ ( x ) < 0.5 } = { t 1 , t 2 , , t r } where t 1 > t 2 > > t r and r 2 . Then, the chain of q -level filters of λ is:
λ q 0.5 λ q t 1 λ q t 2 λ q t r = H .
Define two fuzzy sets μ and ν in H by:
μ ( x ) = t 1 if x λ q t 1 , t n if x λ q t n λ q t n - 1 for n = 2 , 3 , , r ,
and:
ν ( x ) = λ ( x ) if x λ q 0.5 , k if x λ q t 2 λ q 0.5 , t n if x λ q t n λ q t n - 1 for n = 3 , 4 , , r ,
respectively, where k ( t 3 , t 2 ) . Then, μ and ν are ( , q ) -fuzzy filters of H, and μ λ and ν λ . The chains of q -level filters of μ and ν are given by:
μ q t 1 μ q t 2 μ q t r and ν q 0.5 ν q t 2 ν q t r ,
respectively. It is clear that μ ν = λ . This completes the proof.
 □

4. Conclusions

Our aim was to define the concepts of ( , ) -fuzzy filters and ( , q ) -fuzzy filters of hoops, and we discussed some properties and found some equivalent definitions of them. Then, we defined a congruence relation on the hoop by an ( , ) -fuzzy filter of the hoop and proved that the quotient structure of this relation is a hoop. For future works, we will introduce ( α , β ) -fuzzy (positive) implicative filters for ( α , β ) { ( , ) , ( , q ) } of hoops, investigate some of their properties, and try to find some equivalent definitions of them. Furthermore, we study the relation between them. Moreover, we can investigate the corresponding quotients.

Author Contributions

The authors had the same contributions to complete the paper.

Funding

This research received no external funding.

Acknowledgments

The authors wish to thank the anonymous reviewers for their valuable suggestions.

Conflicts of Interest

The authors declare no conflicts of interest.

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Kologani, M.A.; Takallo, M.M.; Kim, H.S. Fuzzy Filters of Hoops Based on Fuzzy Points. Mathematics 2019, 7, 430. https://doi.org/10.3390/math7050430

AMA Style

Kologani MA, Takallo MM, Kim HS. Fuzzy Filters of Hoops Based on Fuzzy Points. Mathematics. 2019; 7(5):430. https://doi.org/10.3390/math7050430

Chicago/Turabian Style

Kologani, Mona Aaly, Mohammad Mohseni Takallo, and Hee Sik Kim. 2019. "Fuzzy Filters of Hoops Based on Fuzzy Points" Mathematics 7, no. 5: 430. https://doi.org/10.3390/math7050430

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