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Article

Alexandrov L-Fuzzy Pre-Proximities

Department of Mathematics, Gangneung-Wonju National University, Gangneung, Gangwondo 25457, Korea
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Mathematics 2019, 7(1), 85; https://doi.org/10.3390/math7010085
Submission received: 1 December 2018 / Revised: 11 January 2019 / Accepted: 11 January 2019 / Published: 15 January 2019
(This article belongs to the Section Mathematics and Computer Science)

Abstract

:
In this paper, we introduce the concepts of Alexandrov L-fuzzy pre-proximities on complete residuated lattices. Moreover, we investigate their relations among Alexandrov L-fuzzy pre-proximities, Alexandrov L-fuzzy topologies, L-fuzzy upper approximate operators, and L-fuzzy lower approximate operators. We give their examples.

1. Introduction

Pawlak [1,2] introduced the concept of rough set theory as a formal tool to deal with imprecision and uncertainty in data analysis. Ward et al. [3] introduced the concept of the complete residuated lattice, which is an algebraic structure for many-valued logic. It is an important mathematical tool for studying algebraic structure. By using lower and upper approximation operators, information systems and decision rules were investigated in complete residuated lattices [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]. Bělohlávek [4] developed the notion of fuzzy contexts using Galois connections with R L X × Y on a complete residuated lattice. El-Dardery [6] introduced L-fuzzy pre-proximity in view points of Sostak’s fuzzy topology [9] and Kim’s L-fuzzy proximities [13] on strictly two-sided, commutative quantales. Kim [10,11,12,13,14,15] investigated the properties of Alexandrov L-fuzzy topologies, Alexandrov L-fuzzy quasi-uniformities, and L-fuzzy approximate operators in complete residuated lattices.
In this paper, we introduce the concepts of Alexandrov L-fuzzy pre-proximities on complete residuated lattices, which are a unified approach to the three spaces: Alexandrov L-fuzzy topologies, L-fuzzy lower approximate operators, and L-fuzzy lower approximate operators as an extension of Pawlak’s rough sets. Moreover, we investigate their relations among Alexandrov L-fuzzy pre-proximities, Alexandrov L-fuzzy topologies, L-fuzzy lower approximate operators, and L-fuzzy lower approximate operators. We give their examples.

2. Preliminaries

Definition 1
([4,8,9,10]). An algebra ( L , , , , , , ) is a complete residuated lattice if:
(L1)
( L , , , , , ) is a complete lattice with the greatest element and the least element ;
(L2)
( L , , ) is a commutative monoid;
(L3)
x y z if and only if x y z for all x , y , z L .
In this paper, we always assume that ( L , , , , , * ) is a complete residuated lattice with an order-reversing involution * , which is defined by:
x y = ( x * y * ) * , x * = x
unless otherwise specified. For all α L ,
( α f ) ( x ) = α f ( x ) , ( α f ) ( x ) = α f ( x ) , α X ( x ) = α ,
x ( y ) = if y = x , , otherwise and x * ( y ) = if y = x , , otherwise .
Lemma 1
([4,7,8]). Let x , y , z , x i , y i , w L . Then, the following hold.
(1)
x = x and x = .
(2)
If y z , then x y x z , x y x z , x y x z , and z x y x .
(3)
x y if and only if x y = .
(4)
( i y i ) * = i y i * and ( i y i ) * = i y i * .
(5)
x ( i y i ) = i ( x y i ) .
(6)
( i x i ) y = i ( x i y ) .
(7)
x ( i y i ) = i ( x y i ) .
(8)
( i x i ) y = i ( x i y ) .
(9)
( x y ) z = x ( y z ) = y ( x z ) .
(10)
x y = ( x y * ) * and x y = x * y .
(11)
( x y ) ( z w ) ( x z ) ( y w ) .
(12)
x y ( x z ) ( y z ) and ( x y ) ( y z ) x z .
(13)
( x y ) ( z w ) ( x z ) ( y w ) .
(14)
x y = y * x * .
(15)
( x y ) ( z w ) ( x z ) ( y w ) ( x z ) ( y w ) .
(16)
i x i i y i i ( x i y i ) and i x i i y i i ( x i y i ) .
(17)
( x y ) ( z w ) ( x z ) ( y w ) .
(18)
x y ( y z ) ( x z ) and x y ( z x ) ( z y ) .
Definition 2
([4]). Let X be a set. A mapping R : X × X L is an L-partial order if:
(E1)
R ( x , x ) = for all x X (reflexive);
(E2)
R ( x , y ) R ( y , z ) R ( x , z ) for all x , y , z X (transitive);
(E3)
if R ( x , y ) = R ( y , x ) = , then x = y (antisymmetric).
Definition 3
([4]). Let X be a set. Define a mapping S : L X × L X L by:
S ( f , g ) = x X ( f ( x ) g ( x ) ) f o r   a l l   f , g L X .
Lemma 2 
([4]). Let f , g , h , k L X , and α L . Then, the following hold.
(1)
S is an L-partial order on L X .
(2)
f g if and only if S ( f , g ) .
(3)
If f g , then S ( h , f ) S ( h , g ) and S ( f , h ) S ( g , h ) .
(4)
S ( f , g ) S ( k , h ) S ( f k , g h ) and S ( f , g ) S ( k , h ) S ( f k , g h ) .
(5)
S ( g , h ) S ( f , g ) S ( f , h ) .
(6)
S ( f , h ) = g L X ( S ( f , g ) S ( g , h ) ) .
Definition 4
([10]). A mapping J : L X L X is an L-lower approximation operator on X if:
(J1)
J ( X ) = X where X ( x ) = for all x X ;
(J2)
J ( f ) f for all f L X ;
(J3)
J ( i Γ f i ) = i Γ J ( f i ) for all { f i } i Γ L X ;
(J4)
J ( α f ) = α J ( f ) .
The pair ( X , J ) is called an L-lower approximation space. An L-lower approximation space is called topological if:
(T)
J ( J ( f ) ) = J ( f ) for all f L X .
Definition 5
([10]). A mapping H : L X L X is an L-upper approximation operator on X if:
(H1)
H ( X ) = X where X ( x ) = for all x X ;
(H2)
H ( f ) f for all f L X ;
(H3)
H ( i Γ f i ) = i Γ H ( f i ) for all { f i } i Γ L X ;
(H4)
H ( α f ) = α H ( f ) .
The pair ( X , H ) is called an L-upper approximation space. An L-upper approximation space is called topological if:
(T)
H ( H ( f ) ) = H ( f ) for all f L X .
Definition 6
([10,11,12]). Let τ be a subset of L X . τ is an Alexandrov L-topology on X if:
(O1)
X , X τ ;
(O2)
If A i τ for all i I , then i I A i , i I τ ;
(O3)
If A τ and α L , then α A , α A τ .
Definition 7
([10]). A mapping T : L X L is an Alexandrov L-fuzzy topology on X if:
(AT1)
T ( X ) = T ( X ) = ;
(AT2)
T ( i f i ) i T ( f i ) and T ( i f i ) i T ( f i ) for all { f i } i Γ L X ;
(AT3)
T ( α f ) T ( f ) and T ( α f ) T ( f ) for all α L and f L X .
The pair ( X , T ) is called an L-fuzzy topological space.
Theorem 1 
([10,11,12]).
(1)
Let J : L X L X be an L-lower approximation operator. Define H J : L X L X by H J ( f ) = J * ( f * ) . Then, H J is an L-upper approximation operator.
(2)
Let H : L X L X be an L-upper approximation operator. Define J H : L X L X by J H ( f ) = H * ( f * ) . Then, J H is an L-lower approximation operator.
(3)
Let T : L X L be an Alexandrov L-fuzzy topology. Define T * : L X L by T * ( f ) = T ( f * ) . Then, T * is an Alexandrov L-fuzzy topology.
(4)
Let τ L X be an Alexandrov L-topology. Define τ * = { f f * τ } . Then, τ * is an Alexandrov L-topology.
Theorem 2
([10]). Let ( X , H ) be an L-upper approximation space. Define a mapping T H : L X L by T H ( f ) = S ( H ( f ) , f ) . Then, T H is an Alexandrov L-fuzzy topology on X with T H * ( f ) = S ( f , J H ( f ) ) where J H ( f ) = H * ( f * ) for all f L X .
Theorem 3
([10]). Let ( X , J ) be an L-lower approximation space. Define a map T J : L X L by T J ( f ) = S ( f , J ( f ) ) . Then, T J is an Alexandrov L-fuzzy topology on X.

3. The Relationships between Alexandrov L-Fuzzy Pre-Proximities and Alexandrov Topological Structures

Definition 8.
A mapping δ : L X × L X L is an Alexandrov L-fuzzy pre-proximity on X if:
(P1)
δ ( X , X ) = δ ( X , X ) = ;
(P2)
δ ( f , g ) x X ( f ( x ) g ( x ) ) ;
(P3)
If f f 1 and g g 1 , then δ ( f , g ) δ ( f 1 , g 1 ) ;
(P4)
For all f i , f , g i , g L X , δ ( i Γ f i , g ) i Γ δ ( f i , g ) and δ ( f , i Γ g i ) i Γ δ ( f , g i ) ;
(P5)
For all α L and f , g L X , δ ( α f , g ) = α δ ( f , g ) = δ ( f , α g ) .
An Alexandrov L-fuzzy pre-proximity δ on X is called an Alexandrov L-fuzzy quasi-proximity if:
(P)
δ ( f , g ) h L X δ ( f , h ) δ ( h * , g ) .
Let δ 1 and δ 2 be two Alexandrov L-fuzzy pre-proximities on X. δ 1 is finer than δ 2 if δ 2 ( f , g ) δ 1 ( f , g ) for all f , g L X .
Example 1.
Let R L X × X . Define a mapping δ : L X × L X L by δ ( f , g ) = x , y X ( R ( x , y ) f ( x ) g ( y ) ) .
(1)
Assume that R is reflexive. Then:
(P1)
δ ( X , X ) = δ ( X , X ) = ;
(P2)
δ ( f , g ) x X ( R ( x , x ) f ( x ) g ( x ) ) = x X ( f ( x ) g ( x ) ) ;
(P3)
If f f 1 and g g 1 , then δ ( f , g ) δ ( f 1 , g 1 ) ;
(P4)
For all f i , f , g i , g L X , δ ( i Γ f i , g ) = i Γ δ ( f i , g ) and δ ( f , i Γ g i ) = i Γ δ ( f , g i ) .
(P5)
For all α L and f , g L X ,
δ ( α f , g ) = x , y X ( R ( x , y ) ( α f ( x ) g ( y ) ) ) = α x , y X ( R ( x , y ) ( f ( x ) g ( y ) ) ) = α δ ( f , g ) .
Hence, δ is an Alexandrov L-fuzzy pre-proximity on X.
(2)
Assume that R is reflexive and transitive. Then, y X ( R ( y , z ) R ( x , y ) ) = R ( x , z ) . For all f , g , h L X , we have by Lemma 1 (17) that:
δ ( f , h ) δ ( h * , g ) = x , y X ( R ( x , y ) f ( x ) h ( y ) ) y , z X ( R ( y , z ) h * ( y ) g ( z ) ) x , y , z X ( R ( x , y ) f ( x ) h ( y ) ) ( R ( y , z ) h * ( y ) g ( z ) ) x , y , z X ( R ( x , y ) R ( y , z ) f ( x ) g ( z ) ) ( h ( y ) h * ( y ) ) = x , y , z X ( R ( x , y ) R ( y , z ) f ( x ) g ( z ) ) = x , z X ( R ( x , z ) f ( x ) g ( z ) ) = δ ( f , g ) .
Thus, δ ( f , g ) h L X ( δ ( f , h ) δ ( h * , g ) ) .
Let h ( y ) = x X ( R ( x , y ) f ( x ) ) * . Then:
h L X ( δ ( f , h ) δ ( h * , g ) ) = h L X ( ( x , y X ( R ( x , y ) f ( x ) h ( y ) ) ) ( y , z X ( R ( y , z ) h * ( y ) g ( z ) ) ) ) ( y X ( h * ( y ) h ( y ) ) ) ( y , z X ( R ( y , z ) x X ( R ( x , y ) f ( x ) g ( z ) ) ) ) = ( x , z X ( y X ( R ( y , z ) R ( x , y ) ) f ( x ) g ( z ) ) ) = x , z X ( R ( x , z ) f ( x ) g ( z ) ) = δ ( f , g ) .
Hence, δ is an Alexandrov L-fuzzy quasi-proximity on X.
By taking R ( x , y ) = X × X , let:
δ 1 ( f , g ) = x , y X ( X × X ( x , y ) f ( x ) g ( y ) ) = x , y X ( f ( x ) g ( y ) ) .
Define Δ X × X L X × X by:
Δ X × X ( x , y ) = if x = y , otherwise .
By taking R ( x , y ) = Δ X × X , let:
δ 2 ( f , g ) = x , y X ( Δ X × X ( x , y ) ( f ( x ) g ( y ) ) ) = x X ( f ( x ) g ( x ) ) .
Then, δ 2 ( f , g ) δ ( f , g ) δ 1 ( f , g ) for all f , g L X .
Lemma 3.
Let δ be an Alexandrov L-fuzzy pre-proximity on X. For all α L and f , g , f i , g i L X , the following hold.
(1)
δ ( i Γ f i , g ) = i Γ δ ( f i , g ) and δ ( f , i Γ g i ) = i Γ δ ( f , g i ) .
(2)
δ ( α f , α g ) δ ( f , g ) and δ ( α f , α g ) δ ( f , g ) .
Proof. 
(1)
It follows from (P3) and (P4).
(2)
It follows from δ ( α f , α g ) = α δ ( f , α g ) = δ ( f , α ( α g ) ) δ ( f , g ) .
 □
Theorem 4.
Let δ be an Alexandrov L-fuzzy pre-proximity on X. Define a mapping δ s : L X × L X L by δ s ( f , g ) = δ ( g , f ) . Then, the following hold.
(1)
δ s is an Alexandrov L-fuzzy pre-proximity on X.
(2)
δ ( f , g ) = x , y X ( δ ( x , y ) ( f ( x ) g ( y ) ) .
(3)
There exists a reflexive L-fuzzy relation R δ L X × X such that:
δ ( f , g ) = x , y X ( R δ ( x , y ) ( f ( x ) g ( y ) ) ) .
(4)
There exists a reflexive L-fuzzy relation R δ s = R δ 1 L X × X such that:
δ s ( f , g ) = x , y X ( R δ 1 ( x , y ) ( f ( x ) g ( y ) ) ) .
Proof. 
(1) It is easily proven.
(2) Since f = x X ( f ( x ) x ) and g = y X ( g ( y ) y ) , we have:
δ ( f , g ) = δ ( x X ( f ( x ) x ) , y X ( g ( y ) y ) ) = x X f ( x ) δ ( x , y X ( g ( y ) y ) ) = x , y X f ( x ) g ( y ) δ ( x , y ) .
(3) Let R δ ( x , y ) = δ ( x , y ) in the equation in (2). By (P2),
R δ ( x , x ) = δ ( x , x ) x X ( x ( x ) x ( x ) ) = .
Moreover, δ ( f , g ) = x , y X ( R δ ( x , y ) f ( x ) g ( y ) ) .
(4) Since R δ s ( x , y ) = δ s ( x , y ) = δ ( y , x ) = R δ 1 ( x , y ) by (2), we have:
δ s ( f , g ) = δ ( g , f ) = x , y X R δ ( x , y ) ( g ( x ) f ( y ) ) = x , y X R δ 1 ( y , x ) ( f ( y ) g ( x ) ) .
 □
Theorem 5.
Let δ be an Alexandrov L-fuzzy pre-proximity on X. Define a mapping T δ : L X L by T δ ( f ) = δ * ( f , f * ) . Then, T δ is an Alexandrov L-fuzzy topology on X such that T δ * = T δ s . If δ 1 δ 2 , then T δ 1 T δ 2 .
Proof. 
(AT1) T δ ( X ) = δ * ( X , X * ) = and T δ ( X ) = δ * ( X , X * ) = .
(AT2) By (P3) and (P4), we have:
T δ ( i f i ) = δ * ( i f i , i f i * ) δ * ( f i , i f i * ) = i δ * ( f i , f i * ) = i T δ ( f i )
and:
T δ ( i f i ) = δ * ( i f i , i f i * ) δ * ( i f i , f i * ) = i δ * ( f i , f i * ) = i T δ ( f i ) .
(AT3) By Lemma 3 (2), we have:
T δ ( α f ) = δ * ( α f , α f * ) = α δ * ( f , α f * ) = δ * ( f , α ( α f * ) ) δ * ( f , f * ) = T δ ( f ) , T δ ( α f ) = δ * ( α f , α f * ) δ * ( f , f * ) = T δ ( f ) .
Then, T δ is an Alexandrov L-fuzzy topology on X. Moreover,
T δ * ( f ) = T δ ( f * ) = δ * ( f * , f ) = δ s * ( f , f * ) = T δ s ( f ) .
 □
Example 2.
Let R L X × X be a reflexive fuzzy relation. Define a mapping δ : L X × L X L by δ ( f , g ) = x , y X ( R ( x , y ) f ( x ) g ( y ) ) . Then:
T δ ( f ) = δ * ( f , f * ) = x , y X ( R ( x , y ) f ( x ) f * ( y ) ) * = x , y X ( R ( x , y ) ( f ( x ) f ( y ) ) .
If R = X × X , then T δ ( f ) = x , y X ( f ( x ) f ( y ) ) .
If R = Δ X × X , then T δ ( f ) = x X ( f ( x ) f ( x ) ) = .
From the following two theorems, we obtain the L-lower approximation operator and the L-lower approximation operator induced by an Alexandrov L-fuzzy pre-proximity.
Theorem 6.
Let δ be an Alexandrov L-fuzzy pre-proximity on X. Define a mapping H δ : L X L X by H δ ( f ) ( x ) = δ ( f , x ) . Then, the following hold.
(1)
H δ is an L-upper approximation operator on X.
(2)
δ ( x , x ) = .
(3)
There exists a reflexive L-fuzzy relation R δ L X × X such that:
H δ ( f ) ( x ) = y X ( R δ ( y , x ) f ( y ) ) .
Moreover, there exists a reflexive L-fuzzy relation R δ s = R δ 1 L X × X such that:
H δ s ( f ) ( x ) = y X ( R δ ( x , y ) f ( y ) ) .
(4)
y X ( δ ( x , y ) δ ( y , z ) ) δ ( x , z ) if and only if H δ is a topological L-upper approximation operator on X.
(5)
T H δ ( f ) = δ * ( f , f * ) = T δ ( f ) for all f L X .
(6)
δ ( f , g ) = x X ( H δ ( f ) ( x ) g ( x ) ) for all f , g L X .
Proof. 
(1)
(H1) Since δ ( X , x ) δ ( X , X ) = , we have H δ ( X ) ( x ) = δ ( X , x ) = .
(H2)
H δ ( f ) ( x ) = δ ( f , x ) x X ( f ( x ) x ( x ) ) = f ( x ) .
(H3)
From Lemma 3, we obtain:
H δ ( i Γ f i ) ( x ) = δ ( i Γ f i , x ) = i Γ δ ( f i , x ) = i Γ H δ ( f i ) ( x ) .
(H4)
By (P4), H δ ( α f ) ( x ) = δ ( α f , x ) = α δ ( f , x ) = α H δ ( f ) . Hence, H δ is an L-upper approximation operator on X.
(2)
δ ( x , x ) x X ( x ( x ) x ( x ) ) = .
(3)
We obtain H δ ( f ) ( x ) = δ ( f , x ) = δ ( y X ( f ( y ) y ) , x ) = y X ( f ( y ) δ ( y , x ) ) . Put R δ ( x , y ) = δ ( x , y ) . By (2), R δ is reflexive. Then, H δ ( f ) ( x ) = y X ( f ( y ) R δ ( y , x ) ) . Moreover, R δ s ( x , y ) = δ s ( x , y ) = δ ( y , x ) = R δ ( y , x ) = R δ 1 ( x , y ) such that:
H δ s ( f ) ( x ) = y X ( f ( y ) δ s * ( y , x ) ) = y X ( f ( y ) δ ( x , y ) ) = y X ( f ( y ) R δ ( x , y ) ) .
(4)
Since H δ ( f ) = y X ( H δ ( f ) ( y ) y ) , we have:
H δ ( H δ ( f ) ) ( x ) = δ ( H δ ( f ) , x ) = δ ( y X ( H δ ( f ) ( y ) y ) , x ) = y X ( H δ ( f ) ( y ) δ ( y , x ) ) = y X ( δ ( f , y ) δ ( y , x ) ) = y X ( δ ( z X ( f ( z ) z ) , y ) δ ( y , x ) ) = y X ( z X ( f ( z ) δ ( z , y ) ) δ ( y , x ) ) = z X ( f ( z ) y X ( δ ( z , y ) δ ( y , x ) ) ) z X ( f ( z ) δ ( z , x ) ) = δ ( z X ( f ( z ) z ) , x ) = δ ( f , x ) = H δ ( f ) ( x ) .
Conversely, since H δ ( H δ ( z ) ) ( x ) H δ ( z ) ( x ) , for H δ ( z ) = y X ( H δ ( z ) ( y ) y ) , we have:
H δ ( H δ ( z ) ) ( x ) = H δ ( y X ( H δ ( z ) ( y ) y ) ) ( x ) = y X ( H δ ( z ) ( y ) H δ ( y ) ( x ) ) H δ ( z ) ( x ) .
(5)
For all f L X , we have:
T H δ ( f ) = S ( H δ ( f ) , f ) = x X ( H δ ( f ) ( x ) f ( x ) ) = x X ( δ ( f , x ) f ( x ) ) = x X ( f * ( x ) δ * ( f , x ) ) = x X δ * ( f , f * ( x ) x ) = δ * ( f , x X ( f * ( x ) x ) ) = δ * ( f , f * ) = T δ ( f ) .
(6)
x X ( H δ ( f ) ( x ) g ( x ) ) = x X ( δ ( f , x ) g ( x ) ) = δ ( f , x X ( x g ( x ) ) ) = δ ( f , g ) .
 □
Theorem 7.
Let δ be an Alexandrov L-fuzzy pre-proximity on X. Define a mapping J δ : L X L X by J δ ( f ) ( x ) = δ * ( x , f * ) . Then, the following hold.
(1)
J δ is an L-lower approximation operator on X.
(2)
There exists a reflexive L-fuzzy relation R δ L X × X such that:
J δ ( f ) ( x ) = y X ( R δ ( x , y ) f ( y ) ) .
Moreover, there exists a reflexive L-fuzzy relation R δ s = R δ 1 L X × X such that:
J δ s ( f ) ( x ) = y X ( R δ ( y , x ) f ( y ) ) .
(3)
For all f L X , y X ( δ ( x , y ) δ ( y , z ) ) δ ( x , z ) if and only if J δ ( J δ ( f ) ) J δ ( f ) .
(4)
T J δ ( f ) = δ * ( f , f * ) = T δ ( f ) for all f L X .
(5)
J δ s ( f ) = δ ( f * , x * ) = H δ * ( f * ) for all f L X and T J δ * = T δ s = T J δ s .
(6)
δ ( f , g ) = S ( f , J δ ( g ) ) for all f , g L X .
Proof. 
(1)
(J1) Since δ * ( x , X * ) δ * ( X , X ) = , we have J δ ( X ) ( x ) = δ * ( x , X * ) = .
(J2)
Note that:
J δ ( f ) ( x ) = δ * ( x , f * ) ( x X ( x ( x ) f * ( x ) ) ) * = f ( x ) .
(J3)
By Lemma 3, we obtain:
J δ ( i Γ f i ) ( x ) = δ * ( x , i Γ f i * ) = i Γ δ * ( x , f i * ) = i Γ J δ ( f i ) ( x ) .
(J4)
By (P4), we have:
J δ ( α f ) ( x ) = δ * ( x , α f * ) = α δ * ( x , f * ) = α J δ ( f ) .
(2)
For f * = y X ( f * ( y ) y ) , we have:
J δ ( f ) ( x ) = δ * ( x , f * ) = δ * ( x , y X ( f * ( y ) y ) ) = y X ( f * ( y ) δ * ( x , y ) ) = y X ( δ ( x , y ) f ( y ) ) .
Let R δ ( x , y ) = δ ( x , y ) . By (2), R δ is reflexive and J δ ( f ) ( x ) = y X ( R δ ( x , y ) f ( y ) ) . Moreover, R δ s ( x , y ) = δ s * ( x , y ) = δ * ( y , x ) = R δ ( y , x ) = R δ 1 ( x , y ) such that:
J δ s ( f ) ( x ) = y X ( δ s * ( x , y ) f ( y ) ) = y X ( δ * ( y , x ) f ( y ) ) = y X ( R δ ( y , x ) f ( y ) ) .
(3)
Since J δ ( f ) = y X ( J δ * ( f ) ( y ) y * ) , we have:
J δ ( J δ ( f ) ) ( x ) = δ * ( x , J δ * ( f ) ) = δ * ( x , y X ( J δ * ( f ) ( y ) y ) ) = y X ( J δ * ( f ) ( y ) δ * ( x , y ) ) = y X ( δ ( y , z X ( f * ( z ) z ) ) δ * ( x , y ) ) = y X ( z X ( f * ( z ) δ ( y , z ) ) δ * ( x , y ) ) = z X ( f * ( z ) y X ( δ ( y , z ) δ ( x , y ) ) ) * y X ( f * ( z ) δ ( x , z ) ) * = δ ( x , y X ( f * ( z ) z ) ) * = δ * ( x , f * ) = J δ ( f ) ( x ) .
Conversely, since J δ ( y * ) ( x ) = δ * ( x , y ) and J δ ( z * ) = y X ( J δ * ( z * ) ( y ) y * ) , we have that J δ ( J δ ( z * ) ) ( x ) = y X ( J δ * ( z * ) ( y ) J δ ( y * ) ( x ) J δ ( z * ) ( x ) if and only if y X ( J δ * ( z * ) ( y ) J δ * ( y * ) ( x ) J δ * ( z * ) ( x ) if and only if y X ( δ ( y , z ) δ ( x , y ) δ ( x , z ) .
(4)
For f = x X ( f ( x ) x ) , we have:
T J δ ( f ) = S ( f , J δ ( f ) ) = x X f ( x ) δ * ( x , f * ) = x X δ * ( f ( x ) x , f * ) ) = δ * ( x X ( f ( x ) x ) , f * ) = δ * ( f , f * ) = T δ ( f ) .
(5)
For all f L X , we have:
J δ s ( f ) ( x ) = δ s * ( x , f * ) = δ * ( f * , x ) = H δ * ( f * ) , T J δ * ( f ) = T J δ ( f * ) = δ * ( f * , f ) = T δ s ( f ) = T J δ s ( f ) .
(6)
For all f , g L X , we have:
S ( f , J δ ( g ) ) = x X ( f ( x ) J δ ( g ) ) ) = x X ( f ( x ) δ * ( x , g * ) ) = δ * ( x X ( f ( x ) x ) , g * ) = δ * ( f , g * ) .
 □
From the following theorem, we obtain the Alexandrov L-fuzzy pre-proximity induced by an L-upper approximation operator.
Theorem 8.
Let ( X , H ) be an L-upper approximation space. Define a mapping δ H : L X × L X L by:
δ H ( f , g ) = y X ( H ( f ) ( y ) g ( y ) ) .
Then, the following hold.
(1)
δ H is an Alexandrov L-fuzzy proximity such that:
δ H ( f , g ) = x , y X ( H ( y ) ( x ) ( f ( y ) g ( x ) ) ) .
(2)
δ H ( f , g ) h L X ( δ H ( f , h ) δ H ( h * , g ) ) . Moreover, the equality holds if H is topological.
(3)
If H is topological, then δ H is an Alexandrov L-fuzzy quasi-proximity on X.
(4)
H = H δ H .
(5)
T H ( f ) = δ H ( f , f ) = T δ H ( f ) for all f L X .
(6)
If δ is an Alexandrov L-fuzzy pre-proximity on X, then δ H δ ( f , g ) = δ ( f , g ) for all f , g L X .
Proof. 
(1)
(P1) Since H ( X ) = X and H ( X ) = X , we have:
δ H ( X , X ) = y X ( H ( X ) ( y ) X ( y ) ) = , δ H ( X , X ) = y X ( H ( X ) ( y ) X ( y ) ) = .
(P2)
Since H ( f ) f , we have:
δ H ( f , g ) = y X ( H ( f ) ( y ) g ( y ) ) x X ( f ( x ) g ( x ) ) .
(P3)
If f f 1 and g g 1 , then H ( f ) H ( f 1 ) . Thus,
δ H ( f , g ) = y X ( H ( f ) ( y ) g ( y ) ) y X ( H ( f 1 ) ( y ) g 1 ( y ) ) = δ H ( f 1 , g 1 ) .
(P4)
Note that:
δ H ( i Γ f i , g ) = x X ( H ( i Γ f i ) ( x ) g ( x ) ) = x X ( i Γ H ( f i ) ( x ) g ( x ) ) = i Γ δ H ( f i , g ) ,
δ H ( f , i Γ g i ) = x X ( f ( x ) i Γ g i ( x ) ) = i Γ δ H ( f , g i )
and:
δ H ( α f , g ) = x X ( H ( α f ) ( x ) g ( x ) ) = x X ( α H ( f ) ( x ) g ( x ) ) = α δ H ( f , g ) .
Hence, δ H is an Alexandrov L-fuzzy pre-proximity. For f = ( f ( y ) y ) , we have:
δ H ( f , g ) = x X ( H ( f ) ( x ) g ( x ) ) = x X ( H ( ( f ( y ) y ) ) ( x ) g ( x ) ) = x X ( y X ( f ( y ) H ( y ) ( x ) ) g ( x ) ) = x , y X ( H ( y ) ( x ) ( f ( y ) g ( x ) ) ) .
(2)
For each f , g , h L X , we have:
δ H ( f , h ) δ H ( h * , g ) = x X ( H ( f ) ( x ) h ( x ) ) x X ( H ( h * ) ( x ) g ( x ) ) x X ( H ( f ) ( x ) h ( x ) ) ( H ( h * ) ( x ) g ( x ) ) x X ( H ( f ) ( x ) f ( x ) ) ( h ( x ) H ( h * ) ( x ) ) by   Lemma   1 ( 17 ) = x X ( H ( f ) ( x ) f ( x ) ) ( h * ( x ) H ( h * ) ( x ) ) = δ H ( f , g ) .
Hence, δ H ( f , g ) h L X ( δ H ( f , h ) δ H ( h * , g ) ) .
If H is topological, then:
h L X ( δ H ( f , h ) δ H ( h * , g ) ) = h L X ( ( x X ( H ( f ( x ) ) h ( x ) ) ) ( x X ( H ( h * ) ( x ) g ( x ) ) ) ) ( p u t h * = H ( f ) , ) ( x X ( H ( f ( x ) ) H * ( f ( x ) ) ) ( x X ( H ( H ( f ) ) ( x ) g ( x ) ) ) ) = ( x X ( H ( H ( f ) ) ( x ) g ( x ) ) ) ) = δ H ( f , g ) .
(3)
It follows by (2).
(4)
For all f L X , we have:
H δ H ( f ) = δ H ( f , x ) = y X ( H ( f ) ( y ) x ( y ) ) = H ( f ) ( x ) .
(5)
For all f L X , we have:
T δ H ( f ) = δ H * ( f , f * ) = x X ( H ( f ) ( x ) f * ( x ) ) * = T H ( f ) .
(6)
For all f , g L X , we have:
δ H δ ( f , g ) = y X ( H δ ( f ) ( y ) g ( y ) ) = y X ( δ ( f , y ) g ( y ) ) = δ ( f , y X ( y g ( y ) ) ) = δ ( f , g ) .
 □
By the above theorem, we obtain the Alexandrov L-fuzzy pre-proximity induced by an L-lower approximation operator in a sense H J ( f ) = J * ( f * ) for all f L X .
Corollary 1.
Let ( X , J ) be an L-lower approximation space. Define a mapping δ J : L X × L X L by:
δ J ( f , g ) = y X ( J * ( f * ) ( y ) g ( y ) ) .
Then, the following hold.
(1)
δ J is an Alexandrov L-fuzzy proximity such that:
δ J ( f , g ) = x , y X ( J * ( y * ) ( x ) ( f ( y ) g ( x ) ) ) .
(2)
δ J ( f , g ) h L X ( δ J ( f , h ) δ J ( h * , g ) ) . Moreover, the equality holds if J is topological.
(3)
If J is topological, then δ J is an Alexandrov L-fuzzy quasi-proximity on X.
(4)
J = J δ J .
(5)
T J ( f ) = δ J ( f , f ) = T δ J ( f ) for all f L X .
(6)
If δ is an Alexandrov L-fuzzy pre-proximity on X, then δ J δ ( f , g ) = δ ( f , g ) for all f , g L X .
Example 3.
Let ( [ 0 , 1 ] , , , * , 0 , 1 ) be a complete residuated lattice [4,8,9,10] where:
x y = max { 0 , x + y 1 } , x y = min { 1 x + y , 1 }
x y = min { x + y , 1 } , x * = 1 x .
Let X = { x , y , z } . Consider the reflexive and transitive L-fuzzy relation R [ 0 , 1 ] X × X defined by:
1 0.7 0.8 0.5 1 0.4 0.6 0.7 1
(1)
By Example 1, we obtain two Alexandrov L-fuzzy quasi-proximities δ , δ s : [ 0 , 1 ] X × [ 0 , 1 ] X [ 0 , 1 ] where:
δ ( f , g ) = x , y X ( R ( x , y ) ( f ( x ) g ( y ) ) ,
δ s ( f , g ) = x , y X ( R ( y , x ) ( f ( x ) g ( y ) ) .
(2)
By Theorem 5, we obtain two Alexandrov L-fuzzy topologies T δ , T δ s : [ 0 , 1 ] X × [ 0 , 1 ] X [ 0 , 1 ] where:
T δ ( f ) = δ * ( f , f * ) = x , y X ( R ( x , y ) ( f ( x ) f * ( y ) ) * = x , y X ( R ( x , y ) ( f ( x ) f * ( y ) ) * ) = x , y X ( R ( x , y ) ( f ( x ) f ( y ) ) ,
T δ s ( f ) = δ * ( f * , f ) = x , y X ( R ( y , x ) ( f ( x ) f ( y ) ) .
(3)
From Theorem 6 (4), since R is a reflexive and transitive L-fuzzy relation, we obtain two topological L-upper approximation operators H δ , H δ s : [ 0 , 1 ] X [ 0 , 1 ] X where:
H δ ( f ) ( x ) = δ ( f , x ) = y X ( R ( y , x ) f ( y ) ) ,
H δ s ( f ) ( x ) = y X ( R ( x , y ) f ( y ) ) .
(4)
By Theorem 6 (4), we obtain two topological L-lower approximation operators J δ , J δ s : [ 0 , 1 ] X [ 0 , 1 ] X where:
J δ ( f ) ( x ) = δ * ( x , f * ) = y X ( R ( x , y ) f ( y ) ) ,
J δ s ( f ) ( x ) = δ * ( f * , x ) = y X ( R ( y , x ) f ( y ) ) .
(5)
From Theorem 8, since H δ and H δ s are topological L-upper approximation operators, we obtain two Alexandrov L-fuzzy quasi-proximities δ H δ , δ H δ s : [ 0 , 1 ] X × [ 0 , 1 ] X [ 0 , 1 ] where:
δ H δ ( f , g ) = y X ( H δ ( f ) ( y ) ( y ) ) = x , y X ( R ( x , y ) f ( x ) ) g ( y ) ) = δ ( f , g ) . δ H δ s ( f , g ) = x , y X ( R ( y , x ) ( f ( x ) g ( y ) ) ) = δ s ( f , g ) .
(6)
By Corollary 1, since J δ and J δ s are topological L-lower approximation operators, we obtain Alexandrov L-fuzzy quasi-proximities δ J δ , δ J δ s : [ 0 , 1 ] X × [ 0 , 1 ] X [ 0 , 1 ] as:
δ J δ ( f , g ) = y X ( J δ * ( f * ) ( y ) ( y ) ) = y X ( ( x X ( R ( y , x ) f * ( x ) ) ) * g ( y ) ) = x , y X ( R ( y , x ) f ( x ) g ( y ) ) = δ s ( f , g ) .
δ J δ s ( f , g ) = y X ( J δ s * ( f * ) ( y ) ( y ) ) = y X ( ( x X ( R ( x , y ) f * ( x ) ) ) * g ( y ) ) = x , y X ( R ( x , y ) f ( x ) g ( y ) ) = δ ( f , g ) .

Author Contributions

All authors have contributed equally to this work.

Funding

This research was funded by Gangneung-Wonju National University.

Acknowledgments

The author would like to thank the editors and the anonymous reviewers for their valuable comments and suggestions which lead to a number of improvements of the paper.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pawlak, Z. Rough sets. Int. J. Comput. Inf. Sci. 1982, 11, 341–356. [Google Scholar] [CrossRef]
  2. Pawlak, Z. Rough Sets: Theoretical Aspects of Reasoning about Data, System Theory, Knowledge Engineering and Problem Solving; Kluwer Academic Publishers: Dordrecht, The Netherlands, 1991. [Google Scholar]
  3. Ward, M.; Dilworth, R.P. Residuated lattices. Trans. Am. Math. Soc. 1939, 45, 335–354. [Google Scholar] [CrossRef]
  4. Bělohlávek, R. Fuzzy Relational Systems; Kluwer Academic Publishers: New York, NY, USA, 2002. [Google Scholar]
  5. Čimoka, D.; Šostak, A.P. L-fuzzy syntopogenous structures, Part I: Fundamentals and application to L-fuzzy topologies, L-fuzzy proximities and L-fuzzy uniformities. Fuzzy Sets Syst. 2013, 232, 74–97. [Google Scholar] [CrossRef]
  6. El-Dardery, M.; Ramadan, A.A.; Kim, Y.C. L-fuzzy topogenous orders and L-fuzzy topologies. J. Intell. Fuzzy Syst. 2013, 24, 601–609. [Google Scholar]
  7. Hájek, P. Metamathematices of Fuzzy Logic; Kluwer Academic Publishers: Dordrecht, The Netherlands, 1998. [Google Scholar]
  8. Höhle, U.; Klement, E.P. Non-Classical Logic and Their Applications to Fuzzy Subsets; Kluwer Academic Publishers: Boston, MA, USA, 1995. [Google Scholar]
  9. Höhle, U.; Rodabaugh, S.E. Mathematics of Fuzzy Sets, Logic, Topology and Measure Theory; The Handbooks of Fuzzy Sets Series; Kluwer Academic Publishers: Dordrecht, The Netherlands, 1999. [Google Scholar]
  10. Kim, Y.C. Join preserving maps, fuzzy preorders and Alexandrov fuzzy topologies. Int. J. Pure Appl. Math. 2014, 92, 703–718. [Google Scholar] [CrossRef]
  11. Kim, Y.C. Join-meet preserving maps and Alexandrov fuzzy topologies. J. Intell. Fuzzy Syst. 2015, 28, 457–467. [Google Scholar]
  12. Kim, Y.C. Join-meet preserving maps and fuzzy preorders. J. Intell. Fuzzy Syst. 2015, 28, 1089–1097. [Google Scholar]
  13. Kim, Y.C.; Kim, Y.S. L-approximation spaces and L-fuzzy quasi-uniform spaces. Inf. Sci. 2009, 179, 2028–2048. [Google Scholar] [CrossRef]
  14. Kim, Y.C.; Min, K.C. L-fuzzy proximities and L-fuzzy topologies. Inf. Sci. 2005, 173, 93–113. [Google Scholar] [CrossRef]
  15. Oh, J.M.; Kim, Y.C. The relations between Alexandrov L-fuzzy pre-uniformities and approximation operators. J. Intell. Fuzzy Syst. 2017, 33, 215–228. [Google Scholar] [CrossRef]
  16. Radzikowska, A.M.; Kerre, E.E. A comparative study of fuzzy rough sets. Fuzzy Sets Syst. 2002, 126, 137–155. [Google Scholar] [CrossRef]
  17. Ramadan, A.A.; Elkordy, E.H.; Kim, Y.C. Perfect L-fuzzy topogenous spaces, L-fuzzy quasi-proximities and L-fuzzy quasi-uniform spaces. J. Intell. Fuzzy Syst. 2015, 28, 2591–2604. [Google Scholar] [CrossRef]
  18. Ramadan, A.A.; Elkordy, E.H.; Kim, Y.C. Relationships between L-fuzzy quasi-uniform structures and L-fuzzy topologies. J. Intell. Fuzzy Syst. 2015, 28, 2319–2327. [Google Scholar] [CrossRef]
  19. Rodabaugh, S.E.; Klement, E.P. Topological and Algebraic Structures in Fuzzy Sets; The Handbook of Recent Developments in the Mathematics of Fuzzy Sets; Kluwer Academic Publishers: Boston, MA, USA; London, UK, 2003. [Google Scholar]

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Kim, Y.C.; Oh, J.-M. Alexandrov L-Fuzzy Pre-Proximities. Mathematics 2019, 7, 85. https://doi.org/10.3390/math7010085

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Kim YC, Oh J-M. Alexandrov L-Fuzzy Pre-Proximities. Mathematics. 2019; 7(1):85. https://doi.org/10.3390/math7010085

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Kim, Yong Chan, and Ju-Mok Oh. 2019. "Alexandrov L-Fuzzy Pre-Proximities" Mathematics 7, no. 1: 85. https://doi.org/10.3390/math7010085

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