SlideShare a Scribd company logo
1 of 12
Download to read offline
http://www.iaeme.com/IJARET/index.asp 350 editor@iaeme.com
International Journal of Advanced Research in Engineering and Technology (IJARET)
Volume 10, Issue 2, March - April 2019, pp. 350-361, Article ID: IJARET_10_02_034
Available online at http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=10&IType=02
ISSN Print: 0976-6480 and ISSN Online: 0976-6499
© IAEME Publication
FUZZY IDEALS AND FUZZY DOT IDEALS ON
BH-ALGEBRAS
K. Anitha
Research Scholar,
PG and Research Department of Mathematics,
Saiva Bhanu Kshatriya College,
Aruppukottai - 626 101, Tamil Nadu, India
Dr. N. Kandaraj
Associate Professor,
PG and Research Department of Mathematics,
Saiva Bhanu Kshatriya College,
Aruppukottai - 626 101, Tamil Nadu, India
ABSTRACT
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results.
Keywords: BH-algebras, BH- Ideals, Fuzzy Dot BH-ideal.
Cite this Article: K. Anitha and Dr. N. Kandaraj, Fuzzy Ideals and Fuzzy Dot Ideals
on Bh-Algebras, International Journal of Advanced Research in Engineering and
Technology, 10(2), 2019, pp 350-361.
http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=10&IType=2
Subject Classification: AMS (2000), 06F35, 03G25, 06D99, 03B47
1 INTRODUCTION
Y. Imai and K. Iseki [1, 2, and 3] introduced two classes of abstract algebras: BCK-algebras
and BCI-algebras. It is known that the class of BCK-algebras is a proper subclass of the class
of BCI-algebras. K. Iseki and S. Tanaka, [7] are introduced Ideal theory of BCK-algebras P.
Bhattacharya, N.P. Mukherjee and L.A. Zadeh [4] are introduced fuzzy relations and fuzzy
groups. The notion of BH-algebras is introduced by Y. B Jun, E. H. Roh and H. S. Kim[9]
Since then, several authors have studied BH-algebras. In particular, Q. Zhang, E. H. Roh and
Y. B. Jun [10] studied the fuzzy theory in BH-algebras. L.A. Zadeh [6] introduced notion of
fuzzy sets and A. Rosenfeld [8] introduced the notion of fuzzy group. O.G. Xi [5] introduced
the notion of fuzzy BCK-algebras. After that, Y.B. Jun and J. Meng [10] studied
Characterization of fuzzy sub algebras by their level sub algebras on BCK-algebras. J. Neggers
and H. S. Kim[11] introduced on d-algebras, M. Akram [12] introduced on fuzzy d-algebras In
this paper we classify the notion of Fuzzy Ideals on BH – algebras and the notion of Fuzzy dot
K. Anitha and Dr. N. Kandaraj
http://www.iaeme.com/IJARET/index.asp 351 editor@iaeme.com
Ideals on BH – algebras. And then we investigate several basic properties which are related to
fuzzy BH-ideals and fuzzy dot BH- ideals
2 PRELIMINARIES
In this section we cite the fundamental definitions that will be used in the sequel:
Definition 2.1 [1, 2, 3]
Let X be a nonempty set with a binary operation ∗ and a constant 0. Then (X, ∗, 0) is called
a BCK-algebra if it satisfies the following conditions
1. ((𝑥 ∗ 𝑦) ∗ (𝑥 ∗ 𝑧)) ∗ (𝑧 ∗ 𝑦) = 0
2.(𝑥 ∗ (𝑥 ∗ 𝑦)) ∗ 𝑦 = 0
3.𝑥 ∗ 𝑥 = 0
4. 𝑥 ∗ 𝑦 = 0, 𝑦 ∗ 𝑥 = 0 ⇒ 𝑥 = 𝑦
5. 0 ∗ 𝑥 = 0 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑥, 𝑦, 𝑧 ∈ 𝑋
Definition 2.2 [1, 2, 3]
Let X be a BCK-algebra and I be a subset of X, then I is called an ideal of X if
(I1) 0∈ 𝐼
(I2) 𝑦 𝑎𝑛𝑑 𝑥 ∗ 𝑦 ∈ 𝐼 ⇒ 𝑥 ∈ 𝐼 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑥, 𝑦 ∈ 𝐼
Definition 2.3 [9, 10]
A nonempty set X with a constant 0 and a binary operation ∗ is called a BH-algebra, if it
satisfies the following axioms
(BH1) 𝑥 ∗ 𝑥 = 0
(BH2) 𝑥 ∗ 0 = 0
(BH3) 𝑥 ∗ 𝑦 = 0 𝑎𝑛𝑑 𝑦 ∗ 𝑥 = 0 ⇒ 𝑥 = 𝑦 for all 𝑥, 𝑦 ∈ 𝑋
Example 2.4
Let X= {0, 1, 2} be a set with the following cayley table
* 0 1 2
0 0 1 1
1 1 0 1
2 2 1 0
Then (X, ∗, 0) is a BH-algebra
Definition 2.5[9, 10]
Let X be a BH-algebra and I be a subset of X, then I is called an ideal of X if
(BHI1) 0∈ 𝐼
(BHI2) 𝑦 𝑎𝑛𝑑 𝑥 ∗ 𝑦 ∈ 𝐼 ⇒ 𝑥 ∈ 𝐼
(BHI3) 𝑥 ∈ 𝐼 and 𝑦 ∈ 𝑋 ⇒ 𝑥 ∗ 𝑦 ∈ 𝐼 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑥, 𝑦 ∈ 𝐼
A mapping 𝑓: 𝑋 → 𝑌 of BH-algebras is called a homomorphism if 𝑓 (𝑥 ∗ 𝑦 ) = 𝑓(𝑥) ∗
𝑓(𝑦) for all 𝑥, 𝑦 𝑋 ∈ 𝑋. Note that if 𝑓 ∶ 𝑋 → 𝑌 is homomorphism of BH-algebras, Then
𝑓 (0) = 0’ . We now review some fuzzy logic concepts. A fuzzy subset of a set X is a function
𝜇 ∶ 𝑋 → [0, 1]. For a fuzzy subset μ of X and t ∈ [0, 1], define U (μ; t) to be the set U (μ; t) =
{x ∈ X | μ(x) ≥ t}. For any fuzzy subsets μ and ν of a set X, we define
(𝜇 ∩ 𝜈)(𝑥) = 𝑚𝑖𝑛{𝜇(𝑥), 𝜈(𝑥)} 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑥 ∈ 𝑋.
Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras
http://www.iaeme.com/IJARET/index.asp 352 editor@iaeme.com
Let 𝑓 ∶ 𝑋 → 𝑌 be a function from a set X to a set Y and let μ be a fuzzy subset of X. The
fuzzy subset v of Y defined by )(yv {
otherwise
Yyyfifx
yfx
0
,)()(sup
1
)(1


 

is called the image of µ under𝑓, denoted by 𝑓(µ). If 𝜈 is a fuzzy subset o𝑓 𝑌, the fuzzy
subset μ of X given by 𝜇(𝑥) = 𝜈(𝑓(𝑥)) for all x ∈ X is called the Preimage of ν under f and is
denoted by 𝑓−1
(𝑣) . A fuzzy subset μ in X has the sup property if for any 𝑇 ⊆ 𝑋 there exists
𝑥0∈ T such that 𝜇(𝑥0) =
)(1
)(sup
yfx
z


 . A fuzzy relation μ on a set X is a fuzzy subset of 𝑋 × 𝑋,
that is, a map 𝜇 ∶ 𝑋 × 𝑋 → [0, 1].
Definition 2.6[4, 6, 8]
Let X be a nonempty set. A fuzzy (sub) set 𝜇 of the set X is a mapping 𝜇: 𝑋 → [0,1
Definition 2.7[4, 6, 8]
Let 𝜇 be the fuzzy set of a set X. For a fixed s∈ [0,1], the set 𝜇 𝑠 = {𝑥 ∈ 𝑋: 𝜇(𝑥) ≥ 𝑠}is
called an upper level of μ or level subset of 𝜇
Definition 2.8[5, 7]
A fuzzy set 𝜇 in X is called fuzzy BCK-ideal of X if it satisfies the following inequalities
1.𝜇(0) ≥ 𝜇(𝑥)
2. 𝜇(𝑥) ≥ min{𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)}
Definition 2.9 [11]
Let X be a nonempty set with a binary operation ∗ and a constant 0. Then (X, ∗, 0) is called
a d - algebra if it satisfies the following axioms.
1.𝑥 ∗ 𝑥 = 0
2. 0 ∗ 𝑥 = 0
3. 𝑥 ∗ 𝑦 = 0, 𝑦 ∗ 𝑥 = 0 ⇒ 𝑥 = 𝑦 for all 𝑥, 𝑦 ∈ 𝑋
Definition 2.10 [12]
A fuzzy set 𝜇 in X is called fuzzy d-ideal of X if it satisfies the following inequalities
Fd1.𝜇(0) ≥ 𝜇(𝑥)
Fd2𝜇(𝑥) ≥ min{𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)}
Fd3. 𝜇(𝑥 ∗ 𝑦) ≥ min{𝜇(𝑥), 𝜇(𝑦)} For all 𝑥, 𝑦 ∈ 𝑋
Definition 2.11[12] A fuzzy subset μ of X is called a fuzzy dot d-ideal of X if it satisfies
The following conditions:
1. 𝜇(0) ≥ 𝜇(𝑥)
2. 𝜇(𝑥) ≥ 𝜇(𝑥 ∗ 𝑦) . 𝜇(𝑦)
3. 𝜇(𝑥 ∗ 𝑦) ≥ 𝜇(𝑥). 𝜇(𝑦)for all 𝑥, 𝑦 ∈ 𝑋
3. FUZZY IDEALS ON BH-ALGEBRAS
Definition 3.1
A fuzzy set 𝜇 in X is called fuzzy BH-ideal of X if it satisfies the following inequalities
1.𝜇(0) ≥ 𝜇(𝑥)
2. 𝜇(𝑥) ≥ min{𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)}
3. 𝜇(𝑥 ∗ 𝑦) ≥ min{𝜇(𝑥), 𝜇(𝑦)} for all 𝑥, 𝑦 ∈ 𝑋
K. Anitha and Dr. N. Kandaraj
http://www.iaeme.com/IJARET/index.asp 353 editor@iaeme.com
Example 3.2
Let X= {0, 1, 2, 3} be a set with the following cayley table
* 0 1 2 3
0 0 0 0 0
1 1 0 0 1
2 2 2 0 0
3 3 3 3 0
Then (X, ∗ ,0) is not BCK-algebra. Since {(1∗ 3) ∗ (1 ∗ 2)} ∗ (2 ∗ 3) = 1 ≠ 0
We define fuzzy set 𝜇 in X by 𝜇(0) = 0.8 and 𝜇(𝑥) = 0.01 for all 𝑥 ≠ 0 in X. then it is
easy to show that 𝜇 is a BH-ideal of X.
We can easily observe the following propositions
1. In a BH-algebra every fuzzy BH-ideal is a fuzzy BCK-ideal, and every fuzzy BCK-
ideal is a fuzzy BH -Sub algebra
2. Every fuzzy BH-ideal of a BH- algebra is a fuzzy BH-subalgebra.
Example 3.3
Let X = {0, 1, 2} be a set given by the following cayley table
* 0 1 2
0 0 0 0
1 1 0 1
2 2 2 0
Then (X, ∗ ,0) is a fuzzy BCK-algebra. We define fuzzy set 𝜇 in X by 𝜇(0) = 0.7, 𝜇(1) =
0.5, 𝜇(2) = 0.2
Then 𝜇 is a fuzzy BH-ideal of X.
Definition 3.4
Let λ 𝑎𝑛𝑑 𝜇 be the fuzzy sets in a set X. The Cartesian product λ × 𝜇: 𝑋 × 𝑋 → [0,1] is
defined by (λ × 𝜇)(𝑥, 𝑦) = min{𝜆(𝑥), 𝜇(𝑦)} ∀𝑥, 𝑦 ∈ 𝑋.
Theorem 3.5
If λ 𝑎𝑛𝑑 𝜇 be the fuzzy BH-ideals of a BH- algebra X, then λ × 𝜇 is a fuzzy BH-ideals
of 𝑋 × 𝑋
Proof
For any (𝑥, 𝑦) ∈ 𝑋 × 𝑋, wehave
(λ × 𝜇)(0,0) = min{𝜆(0), 𝜇(0)} ≥ min{ 𝜆(𝑥), 𝜇(𝑦)}
= (λ × 𝜇)(𝑥, 𝑦)
That is (λ × 𝜇)(0,0) = (λ × 𝜇)(𝑥, 𝑦)
Let (𝑥1 , 𝑥2) 𝑎𝑛𝑑 (𝑦1, 𝑦2) ∈ 𝑋 × 𝑋
Then, (λ × 𝜇) (𝑥1 , 𝑥2) = 𝑚𝑖𝑛{𝜆(𝑥1), 𝜇(𝑥2)}
≥ min{min{ 𝜆(𝑥1 ∗ 𝑦1), 𝜆(𝑦1)} , min{𝜇(𝑥2 ∗ 𝑦2), 𝜇(𝑦2)}
= min{min 𝜆(𝑥1 ∗ 𝑦1 ), 𝜇(𝑥2 ∗ 𝑦2), min{ 𝜆(𝑦1), 𝜇(𝑦2)}}
= min {(λ × 𝜇) (𝑥1 ∗ 𝑦1, 𝑥2 ∗ 𝑦2)) , ( λ × 𝜇) (𝑦1, 𝑦2)}
= min {((λ × 𝜇) (𝑥1, 𝑥2) ∗ (𝑦1, 𝑦2)), ( λ × 𝜇) (𝑦1, 𝑦2)}
That is ((λ × 𝜇) (𝑥1, 𝑥2)) = min {(λ × 𝜇) (𝑥1 , 𝑥2) ∗ (𝑦1, 𝑦2)), (λ × 𝜇)(𝑦1, 𝑦2)}
And (λ × 𝜇)( (𝑥1 , 𝑥2) ∗ (𝑦1, 𝑦2))
Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras
http://www.iaeme.com/IJARET/index.asp 354 editor@iaeme.com
= (λ × 𝜇) (𝑥1 ∗ 𝑦1 , 𝑥2 ∗ 𝑦2)
= min{ 𝜆(𝑥1 ∗ 𝑦1 ), 𝜇(𝑥2 ∗ 𝑦2)}
≥ min {min {λ (𝑥1), λ (𝑦1)}, min {𝜇(𝑥2), 𝜇(𝑦2)}}
= min {min (λ ( 𝑥1 ), 𝜇(𝑥2), min{( λ (𝑦1), 𝜇(𝑦2))}
= min {(λ × 𝜇)(( 𝑥1 , 𝑥2), ( λ × 𝜇)(𝑦1, 𝑦2))
That is (λ × 𝜇)(( 𝑥1 , 𝑥2) ∗ (𝑦1, 𝑦2))
=min {(λ × 𝜇)(( 𝑥1 , 𝑥2), ( λ × 𝜇) (𝑦1, 𝑦2)}
Hence λ × 𝜇 is a fuzzy BH-ideal of X× 𝑋
Theorem 3.6
Let λ 𝑎𝑛𝑑 𝜇 be fuzzy sets in a BH-algebra such that 𝜆 × 𝜇 is a fuzzy BH-ideal of 𝑋 ×
𝑋.Then
i)Either λ(0)≥ λ (x)𝑜𝑟 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋.
ii) If λ (0)≥ λ (x) ∀𝑥 ∈ 𝑋, then either 𝜇(0) ≥ λ(𝑥) or 𝜇(0) ≥ 𝜇(𝑥)
iii) If 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋, then either λ (0)≥ λ (x) or λ (0)≥ µ(x)
Proof
We use reduction to absurdity
i) Assume λ(x)> λ (0) and 𝜇(𝑥) ≥ 𝜇(0) for some 𝑥, 𝑦 ∈ 𝑋.
Then (λ × 𝜇)(𝑥, 𝑦) = min{λ(x), 𝜇(𝑦)}
>min {{λ(0), 𝜇(0)}
= (λ × 𝜇)(0,0)
(λ × 𝜇)(𝑥, 𝑦) > (λ × 𝜇)(0,0) ∀𝑥, 𝑦 ∈ 𝑋
Which is a contradiction to (λ × 𝜇) is a fuzzy BH-ideal of X× 𝑋
Therefore either λ (0)≥ λ (x)𝑜𝑟 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋.
ii) Assume 𝜇(0) < λ(𝑥) and 𝜇(0) < 𝜇(𝑦) for some 𝑥, 𝑦 ∈ 𝑋.
Then (λ × 𝜇)(0,0) = min{λ(0), 𝜇(0)}= 𝜇(0)
And (λ × 𝜇)(𝑥, 𝑦) = min{λ(x), 𝜇(𝑦)}> 𝜇(0)
= (λ × 𝜇)(0,0)
This implies (λ × 𝜇)(𝑥, 𝑦) > and ( λ × 𝜇)(0,0)
Which is a contradiction to λ × 𝜇 is a fuzzy BH-ideal of X× 𝑋
Hence if λ (0)≥ λ (x) ∀𝑥 ∈ 𝑋, 𝑡ℎ𝑒𝑛
Either 𝜇(0) ≥ λ(𝑥) or 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋
iii) Assume λ (0)< λ (x) or λ (0)< µ(y) ∀𝑥, 𝑦 ∈ 𝑋
Then ((λ × 𝜇)(0, 0) = min{λ(0), 𝜇(0)}= 𝜆(0)
And (λ × 𝜇)(𝑥, 𝑦) = min{λ(x), 𝜇(𝑦)}> 𝜆(0)
= (λ × 𝜇)(0,0)
This implies (λ × 𝜇)(𝑥, 𝑦) >(λ × 𝜇)(0,0)
Which is a contradiction to (λ × 𝜇) is a fuzzy BH-ideal of 𝑋 × 𝑋
Hence if 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋 then either λ (0)≥ λ (x) or λ (0)≥ µ(x)
This completes the proof
Theorem 3.7
K. Anitha and Dr. N. Kandaraj
http://www.iaeme.com/IJARET/index.asp 355 editor@iaeme.com
If λ × 𝜇 is a fuzzy BH-idela of 𝑋 × 𝑋 then λ 𝑜𝑟 𝜇 is a fuzzy BH-ideal of X.
Proof
First we prove that 𝜇 is a fuzzy BH-ideal of X.
Given λ × 𝜇 is a fuzzy BH-ideal of 𝑋 × 𝑋, then by theorem 3.6(i), either λ (0)≥
λ (x)𝑜𝑟 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋.
Let 𝜇(0) ≥ 𝜇(𝑥)
By theorem 3.6(iii) then either λ (0)≥ λ (x) or λ (0)≥ µ(x)
Now 𝜇(𝑥) = min{λ(0), 𝜇(𝑥)}
= (λ × 𝜇)(0, 𝑥)
≥ min{ ( (λ × 𝜇)(0, 𝑥) ∗ (0, 𝑦)), (λ × 𝜇)(0, 𝑦)}
= min{ (λ × 𝜇)(0 ∗ 0), 𝑥 ∗ 𝑦),(λ × 𝜇)(0, 𝑦)}
= min{ (λ × 𝜇)(0, 𝑥 ∗ 𝑦),(λ × 𝜇)(0, 𝑦)}
= min{ (λ × 𝜇)(0 ∗ 0), 𝑥 ∗ 𝑦),(λ × 𝜇)(0, 𝑦)}
= min{ 𝜇(𝑥 ∗ 𝑦), ( 𝜇)(𝑦)}
That is 𝜇(𝑥) ≥ min{ 𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)}
𝜇(𝑥 ∗ 𝑦) = min{ λ (0) , 𝜇(𝑥 ∗ 𝑦)}
= (λ × 𝜇)(0, 𝑥 ∗ 𝑦)
= (λ × 𝜇)(0 ∗ 0, 𝑥 ∗ 𝑦)
= (λ × 𝜇)(0, 𝑥) ∗ (0, 𝑦)
𝜇(𝑥 ∗ 𝑦) ≥ min{ (λ × 𝜇)(0, 𝑥), (λ × 𝜇)(0, 𝑦)}
=min{𝜇(𝑥), 𝜇(𝑦)}
That is, 𝜇(𝑥 ∗ 𝑦) ≥ min{𝜇(𝑥), 𝜇(𝑦)}
This proves that 𝜇 is a fuzzy BH-ideal of X.
Secondly to prove that λ is a Fuzzy BH-ideal of X.
Using theorem 4.6(i) and (ii) we get
This completes the proof.
Theorem 3.8
If 𝜇 is a fuzzy BH-idela of 𝑋, then 𝜇 𝑡 is a BH-idela of X for all 𝑡 ∈ [0,1]
Proof
Let 𝜇 be a fuzzy BH-ideal of X,
Then By the definition of BH-ideal
𝜇(0) ≥ 𝜇(𝑥)
𝜇(𝑥) ≥ min{ 𝜇(𝑥 ∗ 𝑦), (𝜇(𝑦)}
𝜇(𝑥 ∗ 𝑦) ≥ min{ 𝜇(𝑥), (𝜇(𝑦)} ∀𝑥, 𝑦 ∈ 𝑋
To prove that 𝜇 𝑡 𝑖𝑠 𝑎 BH-ideal of x.
By the definition of level subset of 𝜇
𝜇 𝑡 = {𝑥/ 𝜇(𝑥) ≥ 𝑡}
Let 𝑥, 𝑦 ∈ 𝜇 𝑡 and 𝜇 is a fuzzy BH-ideal of X.
Since 𝜇(0) ≥ 𝜇(𝑥) ≥ 𝑡 implies 0∈ 𝜇 𝑡, for all 𝑡 ∈ [0,1]
Let 𝑥, 𝑦 ∈ 𝜇 𝑡 and 𝑦 ∈ 𝜇 𝑡
Therefore 𝜇(𝑥 ∗ 𝑦) ≥ 𝑡 and 𝜇(𝑦) ≥ 𝑡
Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras
http://www.iaeme.com/IJARET/index.asp 356 editor@iaeme.com
Now 𝜇(𝑥) ≥ min{ 𝜇(𝑥 ∗ 𝑦), (𝜇(𝑦)}
≥ min{𝑡, 𝑡} ≥ 𝑡
Hence (𝜇(𝑥) ≥ 𝑡
That is 𝑥 ∈ 𝜇 𝑡.
Let 𝑥 ∈ 𝜇 𝑡, 𝑦 ∈ 𝑋
Choose y in X such that 𝜇(𝑦) ≥ 𝑡
Since 𝑥 ∈ 𝜇 𝑡 implies 𝜇(𝑥) ≥ 𝑡
We know that 𝜇(𝑥 ∗ 𝑦) ≥ min{ 𝜇(𝑥), (𝜇(𝑦)}
≥ min{𝑡, 𝑡}
≥ 𝑡
That is 𝜇(𝑥 ∗ 𝑦) ≥ 𝑡 implies 𝑥 ∗ 𝑦 ∈ 𝜇 𝑡
Hence 𝜇 𝑡 is a BH-ideal of X.
Theorem 3.9
If X be a BH-algebra, ∀𝑡 ∈ [0,1] and 𝜇 𝑡 𝑖𝑠 𝑎 𝐵𝐻 −ideal of X, then 𝜇 is a fuzzy BH-ideal of
X.
Proof
Since 𝜇 𝑡 𝑖𝑠 𝑎 𝐵𝐻 −ideal of X
0∈ 𝜇 𝑡
ii) 𝑥 ∗ 𝑦 ∈ 𝜇 𝑡 And 𝑦 ∈ 𝜇 𝑡 implies 𝑥 ∈ 𝜇 𝑡
iii)𝑥 ∈ 𝜇 𝑡, y ∈ 𝑋 implies 𝑥 ∗ 𝑦 ∈ 𝜇 𝑡
To prove that 𝜇 𝑖𝑠 𝑎 𝑓𝑢𝑧𝑧𝑦 BH-ideal of X.
Let 𝑥, 𝑦 ∈ 𝜇 𝑡 then 𝜇(𝑥) ≥ 𝑡 and 𝜇(𝑦) ≥ 𝑡
Let 𝜇(𝑥) = 𝑡1 and 𝜇(𝑦) = 𝑡2
Without loss of generality let 𝑡1 ≤ 𝑡2
Then 𝑥 ∈ 𝜇 𝑡1
Now 𝑥 ∈ 𝜇 𝑡1
and y ∈ 𝑋 𝑖𝑚𝑝𝑙𝑖𝑒𝑠 𝑥 ∗ 𝑦 ∈ 𝜇 𝑡1
That is 𝜇(𝑥 ∗ 𝑦) ≥ 𝑡1
= min {𝑡1, 𝑡2}
= min { 𝜇(𝑥), 𝜇(𝑦)}
𝜇(𝑥 ∗ 𝑦) ≥ min { 𝜇(𝑥), 𝜇(𝑦)}
𝑖𝑖) 𝐿𝑒𝑡 𝜇(0) = 𝜇(𝑥 ∗ 𝑥) ≥ min { 𝜇(𝑥), 𝜇(𝑦)} ≥ 𝜇(𝑥) (by proof (i))
That is 𝜇(0) ≥ 𝜇(𝑥) for all x ∈ 𝑋
iii) Let 𝜇(𝑥) = 𝜇(𝑥 ∗ 𝑦) ∗ (0 ∗ 𝑦))
≥ min{ 𝜇(𝑥 ∗ 𝑦), 𝜇(0 ∗ 𝑦)) (By (i))
≥ min{ 𝜇(𝑥 ∗ 𝑦), min{𝜇(0), 𝜇(𝑦)}
≥ min{ 𝜇(𝑥 ∗ 𝑦),{𝜇(𝑦)) (By (ii))
𝜇(𝑥) ≥ min{ 𝜇(𝑥 ∗ 𝑦),{𝜇(𝑦))
Hence 𝜇 is a fuzzy BH-ideal of X.
Definition 3.10
A fuzzy set 𝜇 in X is said to be fuzzy BH- 𝞆 ideal if 𝜇(𝑥 ∗ 𝑢 ∗ 𝑣 ∗ 𝑦) ≥ min { 𝜇(𝑥), 𝜇(𝑦)}
K. Anitha and Dr. N. Kandaraj
http://www.iaeme.com/IJARET/index.asp 357 editor@iaeme.com
Theorem 3.11
Every Fuzzy BH -ideal is a fuzzy BH- 𝞆- ideal
Proof
It is trivial
Remark
Converse of the above theorem is not true. That is every fuzzy BH-𝞆 -ideal is not true. That
is every fuzzy BH -ideal. Let us prove this by an example
Let X = {0, 1, 2} be a set given by the following cayley table
* 0 1 2
0 0 1 2
1 1 0 1
2 2 2 0
Then (X,∗ ,0) is a BH-algebra. We define fuzzy set: X→ [0,1] by 𝜇(0) = 0.8, 𝜇(𝑥) =
0.2 ∀𝑥 ≠ 0 clearly 𝜇 is a fuzzy BH-ideal of X But 𝜇 is not a BH-𝞆-ideal of X.
For Let 𝑥 = 0 𝑢 = 1 𝑣 = 1 𝑦 = 1
𝜇(𝑥 ∗ 𝑢 ∗ 𝑣 ∗ 𝑦 = 𝜇(0 ∗ 1 ∗ 1 ∗ 1)= 𝜇(1) = 0.2
min{ 𝜇(𝑥), 𝜇(𝑦)} = min{ 𝜇(0), 𝜇(0)}
= 𝜇(0) = 0.8
𝜇(𝑥 ∗ 𝑢 ∗ 𝑣 ∗ 𝑦) ≤min { 𝜇(𝑥), 𝜇(𝑦)}
Hence 𝜇 is not a fuzzy BH-𝞆-ideal of X.
And 𝜇(𝑥 ∗ 𝑦)= 𝜇 (𝑓(𝑎) ∗ 𝑓(𝑏))
≥ 𝜇 (𝑓(𝑎 ∗ 𝑏))
= 𝜇 𝑓
(𝑎 ∗ 𝑏)
≥ min{ 𝜇 𝑓(𝑎), 𝜇 𝑓
(𝑏)}
= min{𝜇(𝑓(𝑎), 𝜇(𝑓(𝑏))}
= min{𝜇(𝑥), 𝜇(𝑦)}
Hence 𝜇(𝑥 ∗ 𝑦) ≥ min{𝜇(𝑥), 𝜇(𝑦)}
Hence 𝜇 is a fuzzy BH- 𝞆 ideal of Y.
4. FUZZY DOT BH-IDEALS OF BH-ALGEBRAS
Definition 4.1. A fuzzy subset μ of X is called a fuzzy dot BH-ideal of X if it satisfies
The following conditions:
(FBH1). 𝜇(0) ≥ 𝜇(𝑥)
(FBH2). 𝜇(𝑥) ≥ 𝜇(𝑥 ∗ 𝑦) . 𝜇(𝑦)
(FBH3). 𝜇(𝑥 ∗ 𝑦) ≥ 𝜇(𝑥). 𝜇(𝑦)for all 𝑥, 𝑦 ∈ 𝑋
Example 4.2. Let X = {0, 1, 2, 3} be a BH-algebra with Cayley table (Table 1) as follows:
(Table 1)
* 0 1 2 3
0 0 0 0 0
1 1 0 0 2
2 2 2 0 0
3 3 3 3 0
Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras
http://www.iaeme.com/IJARET/index.asp 358 editor@iaeme.com
Define 𝜇 ∶ 𝑋 → [0,1] by μ (0) =0.9, μ (a) = μ (b) =0.6, μ (c) =0.3 .It is easy to verify that μ
is a Fuzzy dot BH-ideal of X.
Proposition 4.3. Every fuzzy BH-ideal is a fuzzy dot BH-ideal of a BH-algebra.
Remark. The converse of Proposition 4.3 is not true as shown in the following Example
4.2. Let 𝑋 = {0 ,1 ,2 ,3} be a BH-algebra with Cayley table (Table 1) as follows:
Example 4.4. Let 𝑋 = {0,1, 2} be a BH-algebra with Cayley table (Table 2) as follows:
(Table 2)
* 0 1 2
0 0 0 0
1 1 0 2
2 2 1 0
Define μ: X → [0, 1] by μ (0) =0.8, μ (1) = 0.5, μ (2) =0.4. It is easy to verify that μ is a
fuzzy Dot BH-ideal of X, but not a fuzzy d-ideal of X because
𝜇(𝑥) ≤ min{𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)}
𝜇(1) = min{𝜇(1 ∗ 2), 𝜇(2)}
= 𝜇(2)
Proposition 4.5. Every fuzzy dot BH-ideal of a BH-algebra X is a fuzzy dot subalgebra of
X.
Remark. The converse of Proposition 4.5 is not true as shown in the following
Example:
Example 4.6. Let X be the BH-algebra in Example 4.4 and define μ: X → [0, 1] by
μ (0)= μ (1)=0.9, μ (2)= 0.7. It is easy to verify that μ is a fuzzy dot sub algebra of X, but
not a fuzzy dot BH-ideal of X because μ (2)=0.7 ≤ 0.81=μ (2 ∗1)⋅ μ (1) .
Proposition 4.7. If μ and ν are fuzzy dot BH-ideals of a BH-algebra X, then so is μ ∩ ν.
Proof. Let x, y ∈ X. Then
(𝜇 ∩ 𝜈)(0) = 𝑚𝑖𝑛 {𝜇 (0), 𝜈 (0)}
≥ 𝑚𝑖𝑛 {𝜇(𝑥), 𝜈(𝑥)}
= (𝜇 ∩ 𝜈) (𝑥).
Also, (𝜇 ∩ 𝜈) (𝑥) = 𝑚𝑖𝑛 {𝜇(𝑥), 𝜈(𝑥)}
≥ 𝑚𝑖𝑛 {𝜇(𝑥 ∗ 𝑦) · 𝜇(𝑦), 𝜈(𝑥 ∗ 𝑦) · 𝜈(𝑦)}
≥ (𝑚𝑖𝑛 {𝜇(𝑥 ∗ 𝑦), 𝜈(𝑥 ∗ 𝑦)}) · (𝑚𝑖𝑛 {𝜇(𝑦), 𝜈(𝑦)})
= ((𝜇 ∩ 𝜈) (𝑥 ∗ 𝑦)) · ((𝜇 ∩ 𝜈) (𝑦)).
𝐴𝑛𝑑, (𝜇 ∩ 𝜈) (𝑥 ∗ 𝑦) = 𝑚𝑖𝑛 {𝜇(𝑥 ∗ 𝑦), 𝜈(𝑥 ∗ 𝑦)}
≥ 𝑚𝑖𝑛 {𝜇(𝑥) · 𝜇(𝑦), 𝜈(𝑥) · 𝜈(𝑦)}
≥ (𝑚𝑖𝑛 {𝜇(𝑥), 𝜈(𝑥)}) · (𝑚𝑖𝑛 {𝜇(𝑦), 𝜈(𝑦)})
= ((𝜇 ∩ 𝜈) (𝑥)) · ((𝜇 ∩ 𝜈) (𝑦)).
Hence μ ∩ ν is a fuzzy dot BH-ideal of a d-algebra X.
Theorem 4.8. If each nonempty level subset U (μ; t) of μ is a fuzzy BH-ideal of X then
μ is a fuzzy dot BH-ideal of X, where t ∈[0, 1].
Definition 4.9
K. Anitha and Dr. N. Kandaraj
http://www.iaeme.com/IJARET/index.asp 359 editor@iaeme.com
Let σ be a fuzzy subset of X. The strongest fuzzy σ-relation on BH-algebra X is the fuzzy
subset µσ of X ×X given by 𝜇 𝜎(x, y) = σ(x) · σ(y) for all x, y ∈ X. A fuzzy relation μ on BH-
algebra X is called a Fuzzy σ-product relation if µ(x, y) ≥ σ(x) · σ(y) for all x, y ∈ X. A
fuzzy relation μ on BH-algebra is called a left fuzzy relation on σ if µ(x, y) = σ(x) for all x, y
∈ X.
Note that a left fuzzy relation on σ is a fuzzy σ-product relation.
Remark. The converse of Theorem 4.8 is not true as shown in the following example:
Example 4.10. Let X be the BH-algebra in Example 4.4 and define μ: X → [0, 1] by
μ (0)=0.6, μ (1)=0.7, μ (2)= 0.8. We know that μ is a fuzzy dot BH-ideal of X, but
U (μ; 0.8) = {x ∈X | μ(x) ≥ 0.8} = {2, 2} is not BH-ideal of X since 0∉U (μ; 0.8).
Theorem 4.11. Let 𝑓 ∶ 𝑋 → 𝑋 ′ be an onto homomorphism of BH-algebras, ν be a fuzzy
Dot BH-ideal of Y. Then the Preimage 𝑓−1
(𝑣) of ν under f is a fuzzy dot BH-ideal of X.
Proof. Let x∈ X,
𝑓−1(𝑣)(0) = 𝑣(𝑓(0)) = 𝑣(0′
)
≥ 𝑣(𝑓(𝑥)) = 𝑓−1
(𝑣)(𝑥)
For any x, y∈ X, we have
𝑓−1
(𝑣)(𝑥) = ν (f (x)) ≥ ν (f (x)* f(y)) · ν (f (y))
= ν (f (x* y)) · ν (f (y)) = 𝑓−1
(𝑣)(𝑥 ∗ 𝑦). 𝑓−1(𝑣)(𝑦)
Also,
𝑓−1
(𝑣)(𝑥 ∗ 𝑦)= ν (f (x * y)) = ν (f (x) * f (y))
≥ ν (f (x)) · ν(f (y)) = 𝑓−1
(𝑣)(𝑥). 𝑓−1
(𝑣)(𝑦)
Thus 𝑓−1
(𝑣)is a fuzzy dot BH-ideal of X.
Theorem: 4.12 An onto homomorphic image of a fuzzy dot BH-ideal with the sup
Property is a fuzzy dot BH-ideal.
Theorem 4.13. If λ and μ are fuzzy dot BH-ideal of a BH-algebra X, then λ × μ is a fuzzy
Dot BH-ideal of X × X.
Proof.
Let 𝑥, 𝑦 ∈ 𝑋
λ × μ (0,0)=λ(0), μ(0)
≥ λ(x).μ(y)= (λ × μ) (x, y)
For any 𝑥, 𝑥′
, 𝑦, 𝑦′ ∈ 𝑋 wehave
(λ × µ) (x, y) = λ(x). µ(y)
≥ λ(x ∗ x′). λ(x′))µ(y ∗ y′). µ(y′)
= λ(x ∗ x′). µ(y ∗ y′)). λ(x′). µ(y′)
= (λ× µ)(x, y) ∗ (x′
, y′
)). (λ× µ)(x′
, y′
)
Also (λ× µ)(x, y) ∗ (x′
, y′
)) = (λ× µ)(x ∗ x′) ∗ (y ∗ y′
)).
= λ(x ∗ x′). µ(y ∗ y′)
≥ λ(x). λ(x′
)). ( µ(y). µ(y′))
(λ(x). µ(y)). (λ(x′). µ(y′))
= (λ× µ)(x, y). (λ × µ)(x′, y′)
Hence λ × μ is a fuzzy dot BH-ideal of X × X.
Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras
http://www.iaeme.com/IJARET/index.asp 360 editor@iaeme.com
Theorem 4.14. Let σ be a fuzzy subset of a BH-algebra X and 𝜇 𝜎be the strongest fuzzy
σ -relation on BH-algebra X. Then σ is a fuzzy dot BH-ideal of X if and only if 𝜇 𝜎 is a
Fuzzy dot BH-ideal of X × X.
Proof. Assume that σ is a fuzzy dot BH-ideal of X. For any x, y ∈ X we have
𝜇 𝜎 (0, 0)= σ (0) · σ (0) ≥ σ(x) · σ(y) = 𝜇 𝜎 (x, y).
Let x, x ′, y, y ′∈ X. Then
𝜇 𝜎 ((𝑥, 𝑥 ′) ∗ (𝑦, 𝑦 ′)) · 𝜇 𝜎 (𝑦, 𝑦 ′)
= 𝜇 𝜎 (𝑥 ∗ 𝑦, 𝑥 ′ ∗ 𝑦 ′) · 𝜇 𝜎 (𝑦, 𝑦 ′)
= (𝜎(𝑥 ∗ 𝑦) · 𝜎(𝑥 ′ ∗ 𝑦 ′)) · (𝜎(𝑦) · 𝜎(𝑦 ′))
= (𝜎(𝑥 ∗ 𝑦) · 𝜎(𝑦)) · (𝜎(𝑥 ′ ∗ 𝑦 ′) · 𝜎(𝑦 ′))
≤ 𝜎 (𝑥) · 𝜎(𝑥 ′ ) = 𝜇 𝜎 (𝑥, 𝑥 ′ ). 𝐴𝑛𝑑,
𝜇 𝜎 (x, x ′ )· 𝜇 𝜎 (y, y ′) = (σ(x) · σ(x ′)) · (σ(y) · σ(y ′))
= (σ(x) · σ(y)) · (σ(x ′) · σ(y ′))
≤ 𝜎 (𝑥 ∗ 𝑦) · 𝜎( 𝑥 ′ ∗ 𝑦 ′ )
= 𝜇 𝜎 (𝑥 ∗ 𝑦, 𝑥 ′ ∗ 𝑦 ′) = 𝜇 𝜎 ((𝑥, 𝑥 ′) ∗ (𝑦, 𝑦 ′)).
Thus 𝜇 𝜎 is a fuzzy dot BH-ideal of X × X.
Conversely suppose that 𝜇 𝜎 is a fuzzy dot BH-ideal of X × X. From (FBH1) we get
(σ(0) )2
= σ (0) · σ(0)= 𝑐 (0, 0)
And so σ (0) ≥ σ(x) for all x ∈ X. Also we have
( σ(x) )2
= µσ ((x, x )
≥ µσ ((x, x)*(y, y)). µσ (y, y)
=µσ ((x∗y ), (x ∗ y)). µσ (y, y)
=((σ(x ∗ y) · σ(y)) )2
Which implies that 𝜎(𝑥) ≥ 𝜎(𝑥 ∗ y) · σ(y) for all x, y ∈ X.
Also we have
(𝜎(𝑥 ∗ 𝑦)2
=𝜇 𝜎 ((x∗y ), 𝑥 ∗ 𝑦)
=𝜇 𝜎 ((𝑥, 𝑥) ∗ (𝑦, 𝑦)) ≥ µσ(𝑥, 𝑥). µσ(𝑦, 𝑦)
= (σ(𝑥) · σ( 𝑦 ))2
So 𝜎(𝑥 ∗ 𝑦) ≥ 𝜎(𝑥) · 𝜎(𝑦) for all x, y ∈X.
Therefore σ is a fuzzy dot BH-ideal of X.
Proposition 4.15. Let μ be a left fuzzy relation on a fuzzy subset σ of a BH-algebra X. If
μ is a fuzzy dot BH-ideal of X × X, then σ is a fuzzy dot BH-ideal of a BH-algebra X.
Proof.
Suppose that a left fuzzy relation μ on σ is a fuzzy dot BH-ideal of X × X.
Then
σ (0) = μ (0, z ) ∀z ∈ X
By putting z=0
σ (0) = μ (0,0) ≥ μ (x , y )=σ (x ),
For all x∈ X.
For any x, x ′, y, y ′∈ X
K. Anitha and Dr. N. Kandaraj
http://www.iaeme.com/IJARET/index.asp 361 editor@iaeme.com
σ(x) = µ(x, y) ≥ µ((x, y) ∗ (x′
, y′)). µ(x′, y′)
= µ((x ∗ x′), (y ∗ y′)). µ(y, y′))
= σ(x ∗ x′). σ(x ′)
Also
σ(x ∗ x′).= µ(x ∗ x′
, y ∗ y′) = µ((x, y) ∗ (x′
, y′
))
≥ µ(x, y). µ(x′
, y′
)
=σ(x). σ(𝑥′)
Thus σ is a fuzzy dot BH-ideal of a BH-algebra X.
REFERENCES
[1] Y. Imai and K. Iseki, on axiom systems of propositional calculi XIV, Proc. Japan Acad 42
(1966), 19-22.
[2] K. Iseki, An algebra related with a propositional calculus, Proc. Japan, Acad 42 (1966), 26-29.
[3] Iseki K and Tanaka S: “An introduction to theory of BCK-algebras ”, Math. Japan. 23(1978),
1-26.
[4] P. Bhattacharya and N. P. Mukherjee, Fuzzy relations and fuzzy groups, Inform. Sci. 36(1985),
267-282.
[5] O. G. Xi, Fuzzy BCK-algebras, Math. Japan. 36(1991), 935-942.
[6] L. A. Zadeh, Fuzzy sets, Information Control, 8(1965) 338-353.
[7] K. Iseki and S. Tanaka, Ideal theory of BCK-algebras, Math. Japonica, 21(1976), 351-366.
[8] A. Rosenfeld, Fuzzy groups, J. Math. Anal. Appl. 35 (1971), 512–517.
[9] Y. B. Jun, E. H. Roh and H. S. Kim, On BH-algebras, Scientiae Mathematician 1(1) (1998),
347–354.
[10] Q. Zhang, E. H. Roh and Y. B. Jun, on fuzzy BH-algebras, J. Huanggang Normal Univ. 21(3)
(2001), 14–19.
[11] J. Neggers and H. S. Kim, on d-algebras, Math. Slovaca, 49 (1996), 19-26.
[12] M. Akram, on fuzzy d-algebras, Punjab University Journal of Math.37 (2005), 61-76.

More Related Content

What's hot

Fuzzy Group Ideals and Rings
Fuzzy Group Ideals and RingsFuzzy Group Ideals and Rings
Fuzzy Group Ideals and RingsIJERA Editor
 
An approach to Fuzzy clustering of the iris petals by using Ac-means
An approach to Fuzzy clustering of the iris petals by using Ac-meansAn approach to Fuzzy clustering of the iris petals by using Ac-means
An approach to Fuzzy clustering of the iris petals by using Ac-meansijsc
 
On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...
On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...
On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...IOSR Journals
 
Classical relations and fuzzy relations
Classical relations and fuzzy relationsClassical relations and fuzzy relations
Classical relations and fuzzy relationsBaran Kaynak
 
A common fixed point theorem in cone metric spaces
A common fixed point theorem in cone metric spacesA common fixed point theorem in cone metric spaces
A common fixed point theorem in cone metric spacesAlexander Decker
 
Lecture 13 gram-schmidt inner product spaces - 6.4 6.7
Lecture 13   gram-schmidt  inner product spaces - 6.4 6.7Lecture 13   gram-schmidt  inner product spaces - 6.4 6.7
Lecture 13 gram-schmidt inner product spaces - 6.4 6.7njit-ronbrown
 
Rough set on concept lattice
Rough set on concept latticeRough set on concept lattice
Rough set on concept latticeAlexander Decker
 
Extension principle
Extension principleExtension principle
Extension principleSavo Delić
 
Matroid Basics
Matroid BasicsMatroid Basics
Matroid BasicsASPAK2014
 
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
 
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
 
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
 
a - ANTI FUZZY NEW IDEAL OF PUALGEBRA
a - ANTI FUZZY NEW IDEAL OF PUALGEBRAa - ANTI FUZZY NEW IDEAL OF PUALGEBRA
a - ANTI FUZZY NEW IDEAL OF PUALGEBRAijfls
 

What's hot (17)

Fuzzy Group Ideals and Rings
Fuzzy Group Ideals and RingsFuzzy Group Ideals and Rings
Fuzzy Group Ideals and Rings
 
An approach to Fuzzy clustering of the iris petals by using Ac-means
An approach to Fuzzy clustering of the iris petals by using Ac-meansAn approach to Fuzzy clustering of the iris petals by using Ac-means
An approach to Fuzzy clustering of the iris petals by using Ac-means
 
On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...
On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...
On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...
 
Classical relations and fuzzy relations
Classical relations and fuzzy relationsClassical relations and fuzzy relations
Classical relations and fuzzy relations
 
FUZZY LOGIC
FUZZY LOGICFUZZY LOGIC
FUZZY LOGIC
 
A common fixed point theorem in cone metric spaces
A common fixed point theorem in cone metric spacesA common fixed point theorem in cone metric spaces
A common fixed point theorem in cone metric spaces
 
Ch02 fuzzyrelation
Ch02 fuzzyrelationCh02 fuzzyrelation
Ch02 fuzzyrelation
 
Lecture 13 gram-schmidt inner product spaces - 6.4 6.7
Lecture 13   gram-schmidt  inner product spaces - 6.4 6.7Lecture 13   gram-schmidt  inner product spaces - 6.4 6.7
Lecture 13 gram-schmidt inner product spaces - 6.4 6.7
 
Rough set on concept lattice
Rough set on concept latticeRough set on concept lattice
Rough set on concept lattice
 
41-50
41-5041-50
41-50
 
Extension principle
Extension principleExtension principle
Extension principle
 
L7 fuzzy relations
L7 fuzzy relationsL7 fuzzy relations
L7 fuzzy relations
 
Matroid Basics
Matroid BasicsMatroid Basics
Matroid Basics
 
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
 
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
 
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...
 
a - ANTI FUZZY NEW IDEAL OF PUALGEBRA
a - ANTI FUZZY NEW IDEAL OF PUALGEBRAa - ANTI FUZZY NEW IDEAL OF PUALGEBRA
a - ANTI FUZZY NEW IDEAL OF PUALGEBRA
 

Similar to FUZZY IDEALS AND FUZZY DOT IDEALS ON BH-ALGEBRAS

Intuitionistic Fuzzification of T-Ideals in Bci-Algebras
Intuitionistic Fuzzification of T-Ideals in Bci-AlgebrasIntuitionistic Fuzzification of T-Ideals in Bci-Algebras
Intuitionistic Fuzzification of T-Ideals in Bci-Algebrasiosrjce
 
A Study on Intuitionistic Multi-Anti Fuzzy Subgroups
A Study on Intuitionistic Multi-Anti Fuzzy SubgroupsA Study on Intuitionistic Multi-Anti Fuzzy Subgroups
A Study on Intuitionistic Multi-Anti Fuzzy Subgroupsmathsjournal
 
α -ANTI FUZZY NEW IDEAL OF PUALGEBRA
α -ANTI FUZZY NEW IDEAL OF PUALGEBRAα -ANTI FUZZY NEW IDEAL OF PUALGEBRA
α -ANTI FUZZY NEW IDEAL OF PUALGEBRAWireilla
 
Interval valued intuitionistic fuzzy homomorphism of bf algebras
Interval valued intuitionistic fuzzy homomorphism of bf algebrasInterval valued intuitionistic fuzzy homomorphism of bf algebras
Interval valued intuitionistic fuzzy homomorphism of bf algebrasAlexander Decker
 
Existence Theory for Second Order Nonlinear Functional Random Differential Eq...
Existence Theory for Second Order Nonlinear Functional Random Differential Eq...Existence Theory for Second Order Nonlinear Functional Random Differential Eq...
Existence Theory for Second Order Nonlinear Functional Random Differential Eq...IOSR Journals
 
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS Wireilla
 
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRASCUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRASijfls
 
Semicompatibility and fixed point theorem in fuzzy metric space using implici...
Semicompatibility and fixed point theorem in fuzzy metric space using implici...Semicompatibility and fixed point theorem in fuzzy metric space using implici...
Semicompatibility and fixed point theorem in fuzzy metric space using implici...eSAT Publishing House
 
Semicompatibility and fixed point theorem in fuzzy metric space using implici...
Semicompatibility and fixed point theorem in fuzzy metric space using implici...Semicompatibility and fixed point theorem in fuzzy metric space using implici...
Semicompatibility and fixed point theorem in fuzzy metric space using implici...eSAT Journals
 
8 fixed point theorem in complete fuzzy metric space 8 megha shrivastava
8 fixed point theorem in complete fuzzy metric space 8 megha shrivastava8 fixed point theorem in complete fuzzy metric space 8 megha shrivastava
8 fixed point theorem in complete fuzzy metric space 8 megha shrivastavaBIOLOGICAL FORUM
 
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...mathsjournal
 
Residual Quotient and Annihilator of Intuitionistic Fuzzy Sets of Ring and Mo...
Residual Quotient and Annihilator of Intuitionistic Fuzzy Sets of Ring and Mo...Residual Quotient and Annihilator of Intuitionistic Fuzzy Sets of Ring and Mo...
Residual Quotient and Annihilator of Intuitionistic Fuzzy Sets of Ring and Mo...AIRCC Publishing Corporation
 
Fixed Point Results for Weakly Compatible Mappings in Convex G-Metric Space
Fixed Point Results for Weakly Compatible Mappings in Convex G-Metric SpaceFixed Point Results for Weakly Compatible Mappings in Convex G-Metric Space
Fixed Point Results for Weakly Compatible Mappings in Convex G-Metric Spaceinventionjournals
 
00_1 - Slide Pelengkap (dari Buku Neuro Fuzzy and Soft Computing).ppt
00_1 - Slide Pelengkap (dari Buku Neuro Fuzzy and Soft Computing).ppt00_1 - Slide Pelengkap (dari Buku Neuro Fuzzy and Soft Computing).ppt
00_1 - Slide Pelengkap (dari Buku Neuro Fuzzy and Soft Computing).pptDediTriLaksono1
 
RESIDUAL QUOTIENT AND ANNIHILATOR OF INTUITIONISTIC FUZZY SETS OF RING AND MO...
RESIDUAL QUOTIENT AND ANNIHILATOR OF INTUITIONISTIC FUZZY SETS OF RING AND MO...RESIDUAL QUOTIENT AND ANNIHILATOR OF INTUITIONISTIC FUZZY SETS OF RING AND MO...
RESIDUAL QUOTIENT AND ANNIHILATOR OF INTUITIONISTIC FUZZY SETS OF RING AND MO...AIRCC Publishing Corporation
 
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroups
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX SubgroupsPseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroups
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroupsmathsjournal
 
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...mathsjournal
 
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...mathsjournal
 

Similar to FUZZY IDEALS AND FUZZY DOT IDEALS ON BH-ALGEBRAS (20)

Intuitionistic Fuzzification of T-Ideals in Bci-Algebras
Intuitionistic Fuzzification of T-Ideals in Bci-AlgebrasIntuitionistic Fuzzification of T-Ideals in Bci-Algebras
Intuitionistic Fuzzification of T-Ideals in Bci-Algebras
 
A Study on Intuitionistic Multi-Anti Fuzzy Subgroups
A Study on Intuitionistic Multi-Anti Fuzzy SubgroupsA Study on Intuitionistic Multi-Anti Fuzzy Subgroups
A Study on Intuitionistic Multi-Anti Fuzzy Subgroups
 
α -ANTI FUZZY NEW IDEAL OF PUALGEBRA
α -ANTI FUZZY NEW IDEAL OF PUALGEBRAα -ANTI FUZZY NEW IDEAL OF PUALGEBRA
α -ANTI FUZZY NEW IDEAL OF PUALGEBRA
 
Interval valued intuitionistic fuzzy homomorphism of bf algebras
Interval valued intuitionistic fuzzy homomorphism of bf algebrasInterval valued intuitionistic fuzzy homomorphism of bf algebras
Interval valued intuitionistic fuzzy homomorphism of bf algebras
 
Existence Theory for Second Order Nonlinear Functional Random Differential Eq...
Existence Theory for Second Order Nonlinear Functional Random Differential Eq...Existence Theory for Second Order Nonlinear Functional Random Differential Eq...
Existence Theory for Second Order Nonlinear Functional Random Differential Eq...
 
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
 
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRASCUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
CUBIC STRUCTURES OF MEDIAL IDEAL ON BCI -ALGEBRAS
 
2. Areej Tawfeeq Hameed.pdf
2. Areej Tawfeeq Hameed.pdf2. Areej Tawfeeq Hameed.pdf
2. Areej Tawfeeq Hameed.pdf
 
2. Areej Tawfeeq Hameed.pdf
2. Areej Tawfeeq Hameed.pdf2. Areej Tawfeeq Hameed.pdf
2. Areej Tawfeeq Hameed.pdf
 
Semicompatibility and fixed point theorem in fuzzy metric space using implici...
Semicompatibility and fixed point theorem in fuzzy metric space using implici...Semicompatibility and fixed point theorem in fuzzy metric space using implici...
Semicompatibility and fixed point theorem in fuzzy metric space using implici...
 
Semicompatibility and fixed point theorem in fuzzy metric space using implici...
Semicompatibility and fixed point theorem in fuzzy metric space using implici...Semicompatibility and fixed point theorem in fuzzy metric space using implici...
Semicompatibility and fixed point theorem in fuzzy metric space using implici...
 
8 fixed point theorem in complete fuzzy metric space 8 megha shrivastava
8 fixed point theorem in complete fuzzy metric space 8 megha shrivastava8 fixed point theorem in complete fuzzy metric space 8 megha shrivastava
8 fixed point theorem in complete fuzzy metric space 8 megha shrivastava
 
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...
 
Residual Quotient and Annihilator of Intuitionistic Fuzzy Sets of Ring and Mo...
Residual Quotient and Annihilator of Intuitionistic Fuzzy Sets of Ring and Mo...Residual Quotient and Annihilator of Intuitionistic Fuzzy Sets of Ring and Mo...
Residual Quotient and Annihilator of Intuitionistic Fuzzy Sets of Ring and Mo...
 
Fixed Point Results for Weakly Compatible Mappings in Convex G-Metric Space
Fixed Point Results for Weakly Compatible Mappings in Convex G-Metric SpaceFixed Point Results for Weakly Compatible Mappings in Convex G-Metric Space
Fixed Point Results for Weakly Compatible Mappings in Convex G-Metric Space
 
00_1 - Slide Pelengkap (dari Buku Neuro Fuzzy and Soft Computing).ppt
00_1 - Slide Pelengkap (dari Buku Neuro Fuzzy and Soft Computing).ppt00_1 - Slide Pelengkap (dari Buku Neuro Fuzzy and Soft Computing).ppt
00_1 - Slide Pelengkap (dari Buku Neuro Fuzzy and Soft Computing).ppt
 
RESIDUAL QUOTIENT AND ANNIHILATOR OF INTUITIONISTIC FUZZY SETS OF RING AND MO...
RESIDUAL QUOTIENT AND ANNIHILATOR OF INTUITIONISTIC FUZZY SETS OF RING AND MO...RESIDUAL QUOTIENT AND ANNIHILATOR OF INTUITIONISTIC FUZZY SETS OF RING AND MO...
RESIDUAL QUOTIENT AND ANNIHILATOR OF INTUITIONISTIC FUZZY SETS OF RING AND MO...
 
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroups
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX SubgroupsPseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroups
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroups
 
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
 
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...
 

More from IAEME Publication

IAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdfIAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdfIAEME Publication
 
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
 
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSA STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
 
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSBROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
 
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSDETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
 
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
 
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOVOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
 
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
 
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYVISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
 
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
 
GANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICEGANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICEIAEME Publication
 
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
 
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
 
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
 
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
 
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
 
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
 
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
 
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...IAEME Publication
 
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTA MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
 

More from IAEME Publication (20)

IAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdfIAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdf
 
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
 
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSA STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
 
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSBROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
 
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSDETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
 
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
 
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOVOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
 
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
 
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYVISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
 
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
 
GANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICEGANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICE
 
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
 
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
 
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
 
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
 
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
 
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
 
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
 
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
 
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTA MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
 

Recently uploaded

VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130Suhani Kapoor
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxpurnimasatapathy1234
 
Introduction to Microprocesso programming and interfacing.pptx
Introduction to Microprocesso programming and interfacing.pptxIntroduction to Microprocesso programming and interfacing.pptx
Introduction to Microprocesso programming and interfacing.pptxvipinkmenon1
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSCAESB
 
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVHARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVRajaP95
 
Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.eptoze12
 
Electronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfElectronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfme23b1001
 
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerStudy on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerAnamika Sarkar
 
power system scada applications and uses
power system scada applications and usespower system scada applications and uses
power system scada applications and usesDevarapalliHaritha
 
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSAPPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSKurinjimalarL3
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfAsst.prof M.Gokilavani
 
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)dollysharma2066
 
Artificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxArtificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxbritheesh05
 
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )Tsuyoshi Horigome
 
complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...asadnawaz62
 
Churning of Butter, Factors affecting .
Churning of Butter, Factors affecting  .Churning of Butter, Factors affecting  .
Churning of Butter, Factors affecting .Satyam Kumar
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024hassan khalil
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024Mark Billinghurst
 

Recently uploaded (20)

VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
 
Introduction to Microprocesso programming and interfacing.pptx
Introduction to Microprocesso programming and interfacing.pptxIntroduction to Microprocesso programming and interfacing.pptx
Introduction to Microprocesso programming and interfacing.pptx
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentation
 
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVHARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
 
Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.
 
Electronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfElectronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdf
 
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerStudy on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
 
power system scada applications and uses
power system scada applications and usespower system scada applications and uses
power system scada applications and uses
 
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSAPPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
 
Design and analysis of solar grass cutter.pdf
Design and analysis of solar grass cutter.pdfDesign and analysis of solar grass cutter.pdf
Design and analysis of solar grass cutter.pdf
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
 
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
 
Artificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxArtificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptx
 
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )
 
complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...
 
Churning of Butter, Factors affecting .
Churning of Butter, Factors affecting  .Churning of Butter, Factors affecting  .
Churning of Butter, Factors affecting .
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
 
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024
 

FUZZY IDEALS AND FUZZY DOT IDEALS ON BH-ALGEBRAS

  • 1. http://www.iaeme.com/IJARET/index.asp 350 editor@iaeme.com International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 10, Issue 2, March - April 2019, pp. 350-361, Article ID: IJARET_10_02_034 Available online at http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=10&IType=02 ISSN Print: 0976-6480 and ISSN Online: 0976-6499 © IAEME Publication FUZZY IDEALS AND FUZZY DOT IDEALS ON BH-ALGEBRAS K. Anitha Research Scholar, PG and Research Department of Mathematics, Saiva Bhanu Kshatriya College, Aruppukottai - 626 101, Tamil Nadu, India Dr. N. Kandaraj Associate Professor, PG and Research Department of Mathematics, Saiva Bhanu Kshatriya College, Aruppukottai - 626 101, Tamil Nadu, India ABSTRACT In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion of fuzzy dot Ideals of BH-algebras and investigate some of their results. Keywords: BH-algebras, BH- Ideals, Fuzzy Dot BH-ideal. Cite this Article: K. Anitha and Dr. N. Kandaraj, Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras, International Journal of Advanced Research in Engineering and Technology, 10(2), 2019, pp 350-361. http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=10&IType=2 Subject Classification: AMS (2000), 06F35, 03G25, 06D99, 03B47 1 INTRODUCTION Y. Imai and K. Iseki [1, 2, and 3] introduced two classes of abstract algebras: BCK-algebras and BCI-algebras. It is known that the class of BCK-algebras is a proper subclass of the class of BCI-algebras. K. Iseki and S. Tanaka, [7] are introduced Ideal theory of BCK-algebras P. Bhattacharya, N.P. Mukherjee and L.A. Zadeh [4] are introduced fuzzy relations and fuzzy groups. The notion of BH-algebras is introduced by Y. B Jun, E. H. Roh and H. S. Kim[9] Since then, several authors have studied BH-algebras. In particular, Q. Zhang, E. H. Roh and Y. B. Jun [10] studied the fuzzy theory in BH-algebras. L.A. Zadeh [6] introduced notion of fuzzy sets and A. Rosenfeld [8] introduced the notion of fuzzy group. O.G. Xi [5] introduced the notion of fuzzy BCK-algebras. After that, Y.B. Jun and J. Meng [10] studied Characterization of fuzzy sub algebras by their level sub algebras on BCK-algebras. J. Neggers and H. S. Kim[11] introduced on d-algebras, M. Akram [12] introduced on fuzzy d-algebras In this paper we classify the notion of Fuzzy Ideals on BH – algebras and the notion of Fuzzy dot
  • 2. K. Anitha and Dr. N. Kandaraj http://www.iaeme.com/IJARET/index.asp 351 editor@iaeme.com Ideals on BH – algebras. And then we investigate several basic properties which are related to fuzzy BH-ideals and fuzzy dot BH- ideals 2 PRELIMINARIES In this section we cite the fundamental definitions that will be used in the sequel: Definition 2.1 [1, 2, 3] Let X be a nonempty set with a binary operation ∗ and a constant 0. Then (X, ∗, 0) is called a BCK-algebra if it satisfies the following conditions 1. ((𝑥 ∗ 𝑦) ∗ (𝑥 ∗ 𝑧)) ∗ (𝑧 ∗ 𝑦) = 0 2.(𝑥 ∗ (𝑥 ∗ 𝑦)) ∗ 𝑦 = 0 3.𝑥 ∗ 𝑥 = 0 4. 𝑥 ∗ 𝑦 = 0, 𝑦 ∗ 𝑥 = 0 ⇒ 𝑥 = 𝑦 5. 0 ∗ 𝑥 = 0 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑥, 𝑦, 𝑧 ∈ 𝑋 Definition 2.2 [1, 2, 3] Let X be a BCK-algebra and I be a subset of X, then I is called an ideal of X if (I1) 0∈ 𝐼 (I2) 𝑦 𝑎𝑛𝑑 𝑥 ∗ 𝑦 ∈ 𝐼 ⇒ 𝑥 ∈ 𝐼 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑥, 𝑦 ∈ 𝐼 Definition 2.3 [9, 10] A nonempty set X with a constant 0 and a binary operation ∗ is called a BH-algebra, if it satisfies the following axioms (BH1) 𝑥 ∗ 𝑥 = 0 (BH2) 𝑥 ∗ 0 = 0 (BH3) 𝑥 ∗ 𝑦 = 0 𝑎𝑛𝑑 𝑦 ∗ 𝑥 = 0 ⇒ 𝑥 = 𝑦 for all 𝑥, 𝑦 ∈ 𝑋 Example 2.4 Let X= {0, 1, 2} be a set with the following cayley table * 0 1 2 0 0 1 1 1 1 0 1 2 2 1 0 Then (X, ∗, 0) is a BH-algebra Definition 2.5[9, 10] Let X be a BH-algebra and I be a subset of X, then I is called an ideal of X if (BHI1) 0∈ 𝐼 (BHI2) 𝑦 𝑎𝑛𝑑 𝑥 ∗ 𝑦 ∈ 𝐼 ⇒ 𝑥 ∈ 𝐼 (BHI3) 𝑥 ∈ 𝐼 and 𝑦 ∈ 𝑋 ⇒ 𝑥 ∗ 𝑦 ∈ 𝐼 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑥, 𝑦 ∈ 𝐼 A mapping 𝑓: 𝑋 → 𝑌 of BH-algebras is called a homomorphism if 𝑓 (𝑥 ∗ 𝑦 ) = 𝑓(𝑥) ∗ 𝑓(𝑦) for all 𝑥, 𝑦 𝑋 ∈ 𝑋. Note that if 𝑓 ∶ 𝑋 → 𝑌 is homomorphism of BH-algebras, Then 𝑓 (0) = 0’ . We now review some fuzzy logic concepts. A fuzzy subset of a set X is a function 𝜇 ∶ 𝑋 → [0, 1]. For a fuzzy subset μ of X and t ∈ [0, 1], define U (μ; t) to be the set U (μ; t) = {x ∈ X | μ(x) ≥ t}. For any fuzzy subsets μ and ν of a set X, we define (𝜇 ∩ 𝜈)(𝑥) = 𝑚𝑖𝑛{𝜇(𝑥), 𝜈(𝑥)} 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑥 ∈ 𝑋.
  • 3. Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras http://www.iaeme.com/IJARET/index.asp 352 editor@iaeme.com Let 𝑓 ∶ 𝑋 → 𝑌 be a function from a set X to a set Y and let μ be a fuzzy subset of X. The fuzzy subset v of Y defined by )(yv { otherwise Yyyfifx yfx 0 ,)()(sup 1 )(1      is called the image of µ under𝑓, denoted by 𝑓(µ). If 𝜈 is a fuzzy subset o𝑓 𝑌, the fuzzy subset μ of X given by 𝜇(𝑥) = 𝜈(𝑓(𝑥)) for all x ∈ X is called the Preimage of ν under f and is denoted by 𝑓−1 (𝑣) . A fuzzy subset μ in X has the sup property if for any 𝑇 ⊆ 𝑋 there exists 𝑥0∈ T such that 𝜇(𝑥0) = )(1 )(sup yfx z    . A fuzzy relation μ on a set X is a fuzzy subset of 𝑋 × 𝑋, that is, a map 𝜇 ∶ 𝑋 × 𝑋 → [0, 1]. Definition 2.6[4, 6, 8] Let X be a nonempty set. A fuzzy (sub) set 𝜇 of the set X is a mapping 𝜇: 𝑋 → [0,1 Definition 2.7[4, 6, 8] Let 𝜇 be the fuzzy set of a set X. For a fixed s∈ [0,1], the set 𝜇 𝑠 = {𝑥 ∈ 𝑋: 𝜇(𝑥) ≥ 𝑠}is called an upper level of μ or level subset of 𝜇 Definition 2.8[5, 7] A fuzzy set 𝜇 in X is called fuzzy BCK-ideal of X if it satisfies the following inequalities 1.𝜇(0) ≥ 𝜇(𝑥) 2. 𝜇(𝑥) ≥ min{𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)} Definition 2.9 [11] Let X be a nonempty set with a binary operation ∗ and a constant 0. Then (X, ∗, 0) is called a d - algebra if it satisfies the following axioms. 1.𝑥 ∗ 𝑥 = 0 2. 0 ∗ 𝑥 = 0 3. 𝑥 ∗ 𝑦 = 0, 𝑦 ∗ 𝑥 = 0 ⇒ 𝑥 = 𝑦 for all 𝑥, 𝑦 ∈ 𝑋 Definition 2.10 [12] A fuzzy set 𝜇 in X is called fuzzy d-ideal of X if it satisfies the following inequalities Fd1.𝜇(0) ≥ 𝜇(𝑥) Fd2𝜇(𝑥) ≥ min{𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)} Fd3. 𝜇(𝑥 ∗ 𝑦) ≥ min{𝜇(𝑥), 𝜇(𝑦)} For all 𝑥, 𝑦 ∈ 𝑋 Definition 2.11[12] A fuzzy subset μ of X is called a fuzzy dot d-ideal of X if it satisfies The following conditions: 1. 𝜇(0) ≥ 𝜇(𝑥) 2. 𝜇(𝑥) ≥ 𝜇(𝑥 ∗ 𝑦) . 𝜇(𝑦) 3. 𝜇(𝑥 ∗ 𝑦) ≥ 𝜇(𝑥). 𝜇(𝑦)for all 𝑥, 𝑦 ∈ 𝑋 3. FUZZY IDEALS ON BH-ALGEBRAS Definition 3.1 A fuzzy set 𝜇 in X is called fuzzy BH-ideal of X if it satisfies the following inequalities 1.𝜇(0) ≥ 𝜇(𝑥) 2. 𝜇(𝑥) ≥ min{𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)} 3. 𝜇(𝑥 ∗ 𝑦) ≥ min{𝜇(𝑥), 𝜇(𝑦)} for all 𝑥, 𝑦 ∈ 𝑋
  • 4. K. Anitha and Dr. N. Kandaraj http://www.iaeme.com/IJARET/index.asp 353 editor@iaeme.com Example 3.2 Let X= {0, 1, 2, 3} be a set with the following cayley table * 0 1 2 3 0 0 0 0 0 1 1 0 0 1 2 2 2 0 0 3 3 3 3 0 Then (X, ∗ ,0) is not BCK-algebra. Since {(1∗ 3) ∗ (1 ∗ 2)} ∗ (2 ∗ 3) = 1 ≠ 0 We define fuzzy set 𝜇 in X by 𝜇(0) = 0.8 and 𝜇(𝑥) = 0.01 for all 𝑥 ≠ 0 in X. then it is easy to show that 𝜇 is a BH-ideal of X. We can easily observe the following propositions 1. In a BH-algebra every fuzzy BH-ideal is a fuzzy BCK-ideal, and every fuzzy BCK- ideal is a fuzzy BH -Sub algebra 2. Every fuzzy BH-ideal of a BH- algebra is a fuzzy BH-subalgebra. Example 3.3 Let X = {0, 1, 2} be a set given by the following cayley table * 0 1 2 0 0 0 0 1 1 0 1 2 2 2 0 Then (X, ∗ ,0) is a fuzzy BCK-algebra. We define fuzzy set 𝜇 in X by 𝜇(0) = 0.7, 𝜇(1) = 0.5, 𝜇(2) = 0.2 Then 𝜇 is a fuzzy BH-ideal of X. Definition 3.4 Let λ 𝑎𝑛𝑑 𝜇 be the fuzzy sets in a set X. The Cartesian product λ × 𝜇: 𝑋 × 𝑋 → [0,1] is defined by (λ × 𝜇)(𝑥, 𝑦) = min{𝜆(𝑥), 𝜇(𝑦)} ∀𝑥, 𝑦 ∈ 𝑋. Theorem 3.5 If λ 𝑎𝑛𝑑 𝜇 be the fuzzy BH-ideals of a BH- algebra X, then λ × 𝜇 is a fuzzy BH-ideals of 𝑋 × 𝑋 Proof For any (𝑥, 𝑦) ∈ 𝑋 × 𝑋, wehave (λ × 𝜇)(0,0) = min{𝜆(0), 𝜇(0)} ≥ min{ 𝜆(𝑥), 𝜇(𝑦)} = (λ × 𝜇)(𝑥, 𝑦) That is (λ × 𝜇)(0,0) = (λ × 𝜇)(𝑥, 𝑦) Let (𝑥1 , 𝑥2) 𝑎𝑛𝑑 (𝑦1, 𝑦2) ∈ 𝑋 × 𝑋 Then, (λ × 𝜇) (𝑥1 , 𝑥2) = 𝑚𝑖𝑛{𝜆(𝑥1), 𝜇(𝑥2)} ≥ min{min{ 𝜆(𝑥1 ∗ 𝑦1), 𝜆(𝑦1)} , min{𝜇(𝑥2 ∗ 𝑦2), 𝜇(𝑦2)} = min{min 𝜆(𝑥1 ∗ 𝑦1 ), 𝜇(𝑥2 ∗ 𝑦2), min{ 𝜆(𝑦1), 𝜇(𝑦2)}} = min {(λ × 𝜇) (𝑥1 ∗ 𝑦1, 𝑥2 ∗ 𝑦2)) , ( λ × 𝜇) (𝑦1, 𝑦2)} = min {((λ × 𝜇) (𝑥1, 𝑥2) ∗ (𝑦1, 𝑦2)), ( λ × 𝜇) (𝑦1, 𝑦2)} That is ((λ × 𝜇) (𝑥1, 𝑥2)) = min {(λ × 𝜇) (𝑥1 , 𝑥2) ∗ (𝑦1, 𝑦2)), (λ × 𝜇)(𝑦1, 𝑦2)} And (λ × 𝜇)( (𝑥1 , 𝑥2) ∗ (𝑦1, 𝑦2))
  • 5. Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras http://www.iaeme.com/IJARET/index.asp 354 editor@iaeme.com = (λ × 𝜇) (𝑥1 ∗ 𝑦1 , 𝑥2 ∗ 𝑦2) = min{ 𝜆(𝑥1 ∗ 𝑦1 ), 𝜇(𝑥2 ∗ 𝑦2)} ≥ min {min {λ (𝑥1), λ (𝑦1)}, min {𝜇(𝑥2), 𝜇(𝑦2)}} = min {min (λ ( 𝑥1 ), 𝜇(𝑥2), min{( λ (𝑦1), 𝜇(𝑦2))} = min {(λ × 𝜇)(( 𝑥1 , 𝑥2), ( λ × 𝜇)(𝑦1, 𝑦2)) That is (λ × 𝜇)(( 𝑥1 , 𝑥2) ∗ (𝑦1, 𝑦2)) =min {(λ × 𝜇)(( 𝑥1 , 𝑥2), ( λ × 𝜇) (𝑦1, 𝑦2)} Hence λ × 𝜇 is a fuzzy BH-ideal of X× 𝑋 Theorem 3.6 Let λ 𝑎𝑛𝑑 𝜇 be fuzzy sets in a BH-algebra such that 𝜆 × 𝜇 is a fuzzy BH-ideal of 𝑋 × 𝑋.Then i)Either λ(0)≥ λ (x)𝑜𝑟 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋. ii) If λ (0)≥ λ (x) ∀𝑥 ∈ 𝑋, then either 𝜇(0) ≥ λ(𝑥) or 𝜇(0) ≥ 𝜇(𝑥) iii) If 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋, then either λ (0)≥ λ (x) or λ (0)≥ µ(x) Proof We use reduction to absurdity i) Assume λ(x)> λ (0) and 𝜇(𝑥) ≥ 𝜇(0) for some 𝑥, 𝑦 ∈ 𝑋. Then (λ × 𝜇)(𝑥, 𝑦) = min{λ(x), 𝜇(𝑦)} >min {{λ(0), 𝜇(0)} = (λ × 𝜇)(0,0) (λ × 𝜇)(𝑥, 𝑦) > (λ × 𝜇)(0,0) ∀𝑥, 𝑦 ∈ 𝑋 Which is a contradiction to (λ × 𝜇) is a fuzzy BH-ideal of X× 𝑋 Therefore either λ (0)≥ λ (x)𝑜𝑟 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋. ii) Assume 𝜇(0) < λ(𝑥) and 𝜇(0) < 𝜇(𝑦) for some 𝑥, 𝑦 ∈ 𝑋. Then (λ × 𝜇)(0,0) = min{λ(0), 𝜇(0)}= 𝜇(0) And (λ × 𝜇)(𝑥, 𝑦) = min{λ(x), 𝜇(𝑦)}> 𝜇(0) = (λ × 𝜇)(0,0) This implies (λ × 𝜇)(𝑥, 𝑦) > and ( λ × 𝜇)(0,0) Which is a contradiction to λ × 𝜇 is a fuzzy BH-ideal of X× 𝑋 Hence if λ (0)≥ λ (x) ∀𝑥 ∈ 𝑋, 𝑡ℎ𝑒𝑛 Either 𝜇(0) ≥ λ(𝑥) or 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋 iii) Assume λ (0)< λ (x) or λ (0)< µ(y) ∀𝑥, 𝑦 ∈ 𝑋 Then ((λ × 𝜇)(0, 0) = min{λ(0), 𝜇(0)}= 𝜆(0) And (λ × 𝜇)(𝑥, 𝑦) = min{λ(x), 𝜇(𝑦)}> 𝜆(0) = (λ × 𝜇)(0,0) This implies (λ × 𝜇)(𝑥, 𝑦) >(λ × 𝜇)(0,0) Which is a contradiction to (λ × 𝜇) is a fuzzy BH-ideal of 𝑋 × 𝑋 Hence if 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋 then either λ (0)≥ λ (x) or λ (0)≥ µ(x) This completes the proof Theorem 3.7
  • 6. K. Anitha and Dr. N. Kandaraj http://www.iaeme.com/IJARET/index.asp 355 editor@iaeme.com If λ × 𝜇 is a fuzzy BH-idela of 𝑋 × 𝑋 then λ 𝑜𝑟 𝜇 is a fuzzy BH-ideal of X. Proof First we prove that 𝜇 is a fuzzy BH-ideal of X. Given λ × 𝜇 is a fuzzy BH-ideal of 𝑋 × 𝑋, then by theorem 3.6(i), either λ (0)≥ λ (x)𝑜𝑟 𝜇(0) ≥ 𝜇(𝑥) ∀𝑥 ∈ 𝑋. Let 𝜇(0) ≥ 𝜇(𝑥) By theorem 3.6(iii) then either λ (0)≥ λ (x) or λ (0)≥ µ(x) Now 𝜇(𝑥) = min{λ(0), 𝜇(𝑥)} = (λ × 𝜇)(0, 𝑥) ≥ min{ ( (λ × 𝜇)(0, 𝑥) ∗ (0, 𝑦)), (λ × 𝜇)(0, 𝑦)} = min{ (λ × 𝜇)(0 ∗ 0), 𝑥 ∗ 𝑦),(λ × 𝜇)(0, 𝑦)} = min{ (λ × 𝜇)(0, 𝑥 ∗ 𝑦),(λ × 𝜇)(0, 𝑦)} = min{ (λ × 𝜇)(0 ∗ 0), 𝑥 ∗ 𝑦),(λ × 𝜇)(0, 𝑦)} = min{ 𝜇(𝑥 ∗ 𝑦), ( 𝜇)(𝑦)} That is 𝜇(𝑥) ≥ min{ 𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)} 𝜇(𝑥 ∗ 𝑦) = min{ λ (0) , 𝜇(𝑥 ∗ 𝑦)} = (λ × 𝜇)(0, 𝑥 ∗ 𝑦) = (λ × 𝜇)(0 ∗ 0, 𝑥 ∗ 𝑦) = (λ × 𝜇)(0, 𝑥) ∗ (0, 𝑦) 𝜇(𝑥 ∗ 𝑦) ≥ min{ (λ × 𝜇)(0, 𝑥), (λ × 𝜇)(0, 𝑦)} =min{𝜇(𝑥), 𝜇(𝑦)} That is, 𝜇(𝑥 ∗ 𝑦) ≥ min{𝜇(𝑥), 𝜇(𝑦)} This proves that 𝜇 is a fuzzy BH-ideal of X. Secondly to prove that λ is a Fuzzy BH-ideal of X. Using theorem 4.6(i) and (ii) we get This completes the proof. Theorem 3.8 If 𝜇 is a fuzzy BH-idela of 𝑋, then 𝜇 𝑡 is a BH-idela of X for all 𝑡 ∈ [0,1] Proof Let 𝜇 be a fuzzy BH-ideal of X, Then By the definition of BH-ideal 𝜇(0) ≥ 𝜇(𝑥) 𝜇(𝑥) ≥ min{ 𝜇(𝑥 ∗ 𝑦), (𝜇(𝑦)} 𝜇(𝑥 ∗ 𝑦) ≥ min{ 𝜇(𝑥), (𝜇(𝑦)} ∀𝑥, 𝑦 ∈ 𝑋 To prove that 𝜇 𝑡 𝑖𝑠 𝑎 BH-ideal of x. By the definition of level subset of 𝜇 𝜇 𝑡 = {𝑥/ 𝜇(𝑥) ≥ 𝑡} Let 𝑥, 𝑦 ∈ 𝜇 𝑡 and 𝜇 is a fuzzy BH-ideal of X. Since 𝜇(0) ≥ 𝜇(𝑥) ≥ 𝑡 implies 0∈ 𝜇 𝑡, for all 𝑡 ∈ [0,1] Let 𝑥, 𝑦 ∈ 𝜇 𝑡 and 𝑦 ∈ 𝜇 𝑡 Therefore 𝜇(𝑥 ∗ 𝑦) ≥ 𝑡 and 𝜇(𝑦) ≥ 𝑡
  • 7. Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras http://www.iaeme.com/IJARET/index.asp 356 editor@iaeme.com Now 𝜇(𝑥) ≥ min{ 𝜇(𝑥 ∗ 𝑦), (𝜇(𝑦)} ≥ min{𝑡, 𝑡} ≥ 𝑡 Hence (𝜇(𝑥) ≥ 𝑡 That is 𝑥 ∈ 𝜇 𝑡. Let 𝑥 ∈ 𝜇 𝑡, 𝑦 ∈ 𝑋 Choose y in X such that 𝜇(𝑦) ≥ 𝑡 Since 𝑥 ∈ 𝜇 𝑡 implies 𝜇(𝑥) ≥ 𝑡 We know that 𝜇(𝑥 ∗ 𝑦) ≥ min{ 𝜇(𝑥), (𝜇(𝑦)} ≥ min{𝑡, 𝑡} ≥ 𝑡 That is 𝜇(𝑥 ∗ 𝑦) ≥ 𝑡 implies 𝑥 ∗ 𝑦 ∈ 𝜇 𝑡 Hence 𝜇 𝑡 is a BH-ideal of X. Theorem 3.9 If X be a BH-algebra, ∀𝑡 ∈ [0,1] and 𝜇 𝑡 𝑖𝑠 𝑎 𝐵𝐻 −ideal of X, then 𝜇 is a fuzzy BH-ideal of X. Proof Since 𝜇 𝑡 𝑖𝑠 𝑎 𝐵𝐻 −ideal of X 0∈ 𝜇 𝑡 ii) 𝑥 ∗ 𝑦 ∈ 𝜇 𝑡 And 𝑦 ∈ 𝜇 𝑡 implies 𝑥 ∈ 𝜇 𝑡 iii)𝑥 ∈ 𝜇 𝑡, y ∈ 𝑋 implies 𝑥 ∗ 𝑦 ∈ 𝜇 𝑡 To prove that 𝜇 𝑖𝑠 𝑎 𝑓𝑢𝑧𝑧𝑦 BH-ideal of X. Let 𝑥, 𝑦 ∈ 𝜇 𝑡 then 𝜇(𝑥) ≥ 𝑡 and 𝜇(𝑦) ≥ 𝑡 Let 𝜇(𝑥) = 𝑡1 and 𝜇(𝑦) = 𝑡2 Without loss of generality let 𝑡1 ≤ 𝑡2 Then 𝑥 ∈ 𝜇 𝑡1 Now 𝑥 ∈ 𝜇 𝑡1 and y ∈ 𝑋 𝑖𝑚𝑝𝑙𝑖𝑒𝑠 𝑥 ∗ 𝑦 ∈ 𝜇 𝑡1 That is 𝜇(𝑥 ∗ 𝑦) ≥ 𝑡1 = min {𝑡1, 𝑡2} = min { 𝜇(𝑥), 𝜇(𝑦)} 𝜇(𝑥 ∗ 𝑦) ≥ min { 𝜇(𝑥), 𝜇(𝑦)} 𝑖𝑖) 𝐿𝑒𝑡 𝜇(0) = 𝜇(𝑥 ∗ 𝑥) ≥ min { 𝜇(𝑥), 𝜇(𝑦)} ≥ 𝜇(𝑥) (by proof (i)) That is 𝜇(0) ≥ 𝜇(𝑥) for all x ∈ 𝑋 iii) Let 𝜇(𝑥) = 𝜇(𝑥 ∗ 𝑦) ∗ (0 ∗ 𝑦)) ≥ min{ 𝜇(𝑥 ∗ 𝑦), 𝜇(0 ∗ 𝑦)) (By (i)) ≥ min{ 𝜇(𝑥 ∗ 𝑦), min{𝜇(0), 𝜇(𝑦)} ≥ min{ 𝜇(𝑥 ∗ 𝑦),{𝜇(𝑦)) (By (ii)) 𝜇(𝑥) ≥ min{ 𝜇(𝑥 ∗ 𝑦),{𝜇(𝑦)) Hence 𝜇 is a fuzzy BH-ideal of X. Definition 3.10 A fuzzy set 𝜇 in X is said to be fuzzy BH- 𝞆 ideal if 𝜇(𝑥 ∗ 𝑢 ∗ 𝑣 ∗ 𝑦) ≥ min { 𝜇(𝑥), 𝜇(𝑦)}
  • 8. K. Anitha and Dr. N. Kandaraj http://www.iaeme.com/IJARET/index.asp 357 editor@iaeme.com Theorem 3.11 Every Fuzzy BH -ideal is a fuzzy BH- 𝞆- ideal Proof It is trivial Remark Converse of the above theorem is not true. That is every fuzzy BH-𝞆 -ideal is not true. That is every fuzzy BH -ideal. Let us prove this by an example Let X = {0, 1, 2} be a set given by the following cayley table * 0 1 2 0 0 1 2 1 1 0 1 2 2 2 0 Then (X,∗ ,0) is a BH-algebra. We define fuzzy set: X→ [0,1] by 𝜇(0) = 0.8, 𝜇(𝑥) = 0.2 ∀𝑥 ≠ 0 clearly 𝜇 is a fuzzy BH-ideal of X But 𝜇 is not a BH-𝞆-ideal of X. For Let 𝑥 = 0 𝑢 = 1 𝑣 = 1 𝑦 = 1 𝜇(𝑥 ∗ 𝑢 ∗ 𝑣 ∗ 𝑦 = 𝜇(0 ∗ 1 ∗ 1 ∗ 1)= 𝜇(1) = 0.2 min{ 𝜇(𝑥), 𝜇(𝑦)} = min{ 𝜇(0), 𝜇(0)} = 𝜇(0) = 0.8 𝜇(𝑥 ∗ 𝑢 ∗ 𝑣 ∗ 𝑦) ≤min { 𝜇(𝑥), 𝜇(𝑦)} Hence 𝜇 is not a fuzzy BH-𝞆-ideal of X. And 𝜇(𝑥 ∗ 𝑦)= 𝜇 (𝑓(𝑎) ∗ 𝑓(𝑏)) ≥ 𝜇 (𝑓(𝑎 ∗ 𝑏)) = 𝜇 𝑓 (𝑎 ∗ 𝑏) ≥ min{ 𝜇 𝑓(𝑎), 𝜇 𝑓 (𝑏)} = min{𝜇(𝑓(𝑎), 𝜇(𝑓(𝑏))} = min{𝜇(𝑥), 𝜇(𝑦)} Hence 𝜇(𝑥 ∗ 𝑦) ≥ min{𝜇(𝑥), 𝜇(𝑦)} Hence 𝜇 is a fuzzy BH- 𝞆 ideal of Y. 4. FUZZY DOT BH-IDEALS OF BH-ALGEBRAS Definition 4.1. A fuzzy subset μ of X is called a fuzzy dot BH-ideal of X if it satisfies The following conditions: (FBH1). 𝜇(0) ≥ 𝜇(𝑥) (FBH2). 𝜇(𝑥) ≥ 𝜇(𝑥 ∗ 𝑦) . 𝜇(𝑦) (FBH3). 𝜇(𝑥 ∗ 𝑦) ≥ 𝜇(𝑥). 𝜇(𝑦)for all 𝑥, 𝑦 ∈ 𝑋 Example 4.2. Let X = {0, 1, 2, 3} be a BH-algebra with Cayley table (Table 1) as follows: (Table 1) * 0 1 2 3 0 0 0 0 0 1 1 0 0 2 2 2 2 0 0 3 3 3 3 0
  • 9. Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras http://www.iaeme.com/IJARET/index.asp 358 editor@iaeme.com Define 𝜇 ∶ 𝑋 → [0,1] by μ (0) =0.9, μ (a) = μ (b) =0.6, μ (c) =0.3 .It is easy to verify that μ is a Fuzzy dot BH-ideal of X. Proposition 4.3. Every fuzzy BH-ideal is a fuzzy dot BH-ideal of a BH-algebra. Remark. The converse of Proposition 4.3 is not true as shown in the following Example 4.2. Let 𝑋 = {0 ,1 ,2 ,3} be a BH-algebra with Cayley table (Table 1) as follows: Example 4.4. Let 𝑋 = {0,1, 2} be a BH-algebra with Cayley table (Table 2) as follows: (Table 2) * 0 1 2 0 0 0 0 1 1 0 2 2 2 1 0 Define μ: X → [0, 1] by μ (0) =0.8, μ (1) = 0.5, μ (2) =0.4. It is easy to verify that μ is a fuzzy Dot BH-ideal of X, but not a fuzzy d-ideal of X because 𝜇(𝑥) ≤ min{𝜇(𝑥 ∗ 𝑦), 𝜇(𝑦)} 𝜇(1) = min{𝜇(1 ∗ 2), 𝜇(2)} = 𝜇(2) Proposition 4.5. Every fuzzy dot BH-ideal of a BH-algebra X is a fuzzy dot subalgebra of X. Remark. The converse of Proposition 4.5 is not true as shown in the following Example: Example 4.6. Let X be the BH-algebra in Example 4.4 and define μ: X → [0, 1] by μ (0)= μ (1)=0.9, μ (2)= 0.7. It is easy to verify that μ is a fuzzy dot sub algebra of X, but not a fuzzy dot BH-ideal of X because μ (2)=0.7 ≤ 0.81=μ (2 ∗1)⋅ μ (1) . Proposition 4.7. If μ and ν are fuzzy dot BH-ideals of a BH-algebra X, then so is μ ∩ ν. Proof. Let x, y ∈ X. Then (𝜇 ∩ 𝜈)(0) = 𝑚𝑖𝑛 {𝜇 (0), 𝜈 (0)} ≥ 𝑚𝑖𝑛 {𝜇(𝑥), 𝜈(𝑥)} = (𝜇 ∩ 𝜈) (𝑥). Also, (𝜇 ∩ 𝜈) (𝑥) = 𝑚𝑖𝑛 {𝜇(𝑥), 𝜈(𝑥)} ≥ 𝑚𝑖𝑛 {𝜇(𝑥 ∗ 𝑦) · 𝜇(𝑦), 𝜈(𝑥 ∗ 𝑦) · 𝜈(𝑦)} ≥ (𝑚𝑖𝑛 {𝜇(𝑥 ∗ 𝑦), 𝜈(𝑥 ∗ 𝑦)}) · (𝑚𝑖𝑛 {𝜇(𝑦), 𝜈(𝑦)}) = ((𝜇 ∩ 𝜈) (𝑥 ∗ 𝑦)) · ((𝜇 ∩ 𝜈) (𝑦)). 𝐴𝑛𝑑, (𝜇 ∩ 𝜈) (𝑥 ∗ 𝑦) = 𝑚𝑖𝑛 {𝜇(𝑥 ∗ 𝑦), 𝜈(𝑥 ∗ 𝑦)} ≥ 𝑚𝑖𝑛 {𝜇(𝑥) · 𝜇(𝑦), 𝜈(𝑥) · 𝜈(𝑦)} ≥ (𝑚𝑖𝑛 {𝜇(𝑥), 𝜈(𝑥)}) · (𝑚𝑖𝑛 {𝜇(𝑦), 𝜈(𝑦)}) = ((𝜇 ∩ 𝜈) (𝑥)) · ((𝜇 ∩ 𝜈) (𝑦)). Hence μ ∩ ν is a fuzzy dot BH-ideal of a d-algebra X. Theorem 4.8. If each nonempty level subset U (μ; t) of μ is a fuzzy BH-ideal of X then μ is a fuzzy dot BH-ideal of X, where t ∈[0, 1]. Definition 4.9
  • 10. K. Anitha and Dr. N. Kandaraj http://www.iaeme.com/IJARET/index.asp 359 editor@iaeme.com Let σ be a fuzzy subset of X. The strongest fuzzy σ-relation on BH-algebra X is the fuzzy subset µσ of X ×X given by 𝜇 𝜎(x, y) = σ(x) · σ(y) for all x, y ∈ X. A fuzzy relation μ on BH- algebra X is called a Fuzzy σ-product relation if µ(x, y) ≥ σ(x) · σ(y) for all x, y ∈ X. A fuzzy relation μ on BH-algebra is called a left fuzzy relation on σ if µ(x, y) = σ(x) for all x, y ∈ X. Note that a left fuzzy relation on σ is a fuzzy σ-product relation. Remark. The converse of Theorem 4.8 is not true as shown in the following example: Example 4.10. Let X be the BH-algebra in Example 4.4 and define μ: X → [0, 1] by μ (0)=0.6, μ (1)=0.7, μ (2)= 0.8. We know that μ is a fuzzy dot BH-ideal of X, but U (μ; 0.8) = {x ∈X | μ(x) ≥ 0.8} = {2, 2} is not BH-ideal of X since 0∉U (μ; 0.8). Theorem 4.11. Let 𝑓 ∶ 𝑋 → 𝑋 ′ be an onto homomorphism of BH-algebras, ν be a fuzzy Dot BH-ideal of Y. Then the Preimage 𝑓−1 (𝑣) of ν under f is a fuzzy dot BH-ideal of X. Proof. Let x∈ X, 𝑓−1(𝑣)(0) = 𝑣(𝑓(0)) = 𝑣(0′ ) ≥ 𝑣(𝑓(𝑥)) = 𝑓−1 (𝑣)(𝑥) For any x, y∈ X, we have 𝑓−1 (𝑣)(𝑥) = ν (f (x)) ≥ ν (f (x)* f(y)) · ν (f (y)) = ν (f (x* y)) · ν (f (y)) = 𝑓−1 (𝑣)(𝑥 ∗ 𝑦). 𝑓−1(𝑣)(𝑦) Also, 𝑓−1 (𝑣)(𝑥 ∗ 𝑦)= ν (f (x * y)) = ν (f (x) * f (y)) ≥ ν (f (x)) · ν(f (y)) = 𝑓−1 (𝑣)(𝑥). 𝑓−1 (𝑣)(𝑦) Thus 𝑓−1 (𝑣)is a fuzzy dot BH-ideal of X. Theorem: 4.12 An onto homomorphic image of a fuzzy dot BH-ideal with the sup Property is a fuzzy dot BH-ideal. Theorem 4.13. If λ and μ are fuzzy dot BH-ideal of a BH-algebra X, then λ × μ is a fuzzy Dot BH-ideal of X × X. Proof. Let 𝑥, 𝑦 ∈ 𝑋 λ × μ (0,0)=λ(0), μ(0) ≥ λ(x).μ(y)= (λ × μ) (x, y) For any 𝑥, 𝑥′ , 𝑦, 𝑦′ ∈ 𝑋 wehave (λ × µ) (x, y) = λ(x). µ(y) ≥ λ(x ∗ x′). λ(x′))µ(y ∗ y′). µ(y′) = λ(x ∗ x′). µ(y ∗ y′)). λ(x′). µ(y′) = (λ× µ)(x, y) ∗ (x′ , y′ )). (λ× µ)(x′ , y′ ) Also (λ× µ)(x, y) ∗ (x′ , y′ )) = (λ× µ)(x ∗ x′) ∗ (y ∗ y′ )). = λ(x ∗ x′). µ(y ∗ y′) ≥ λ(x). λ(x′ )). ( µ(y). µ(y′)) (λ(x). µ(y)). (λ(x′). µ(y′)) = (λ× µ)(x, y). (λ × µ)(x′, y′) Hence λ × μ is a fuzzy dot BH-ideal of X × X.
  • 11. Fuzzy Ideals and Fuzzy Dot Ideals on Bh-Algebras http://www.iaeme.com/IJARET/index.asp 360 editor@iaeme.com Theorem 4.14. Let σ be a fuzzy subset of a BH-algebra X and 𝜇 𝜎be the strongest fuzzy σ -relation on BH-algebra X. Then σ is a fuzzy dot BH-ideal of X if and only if 𝜇 𝜎 is a Fuzzy dot BH-ideal of X × X. Proof. Assume that σ is a fuzzy dot BH-ideal of X. For any x, y ∈ X we have 𝜇 𝜎 (0, 0)= σ (0) · σ (0) ≥ σ(x) · σ(y) = 𝜇 𝜎 (x, y). Let x, x ′, y, y ′∈ X. Then 𝜇 𝜎 ((𝑥, 𝑥 ′) ∗ (𝑦, 𝑦 ′)) · 𝜇 𝜎 (𝑦, 𝑦 ′) = 𝜇 𝜎 (𝑥 ∗ 𝑦, 𝑥 ′ ∗ 𝑦 ′) · 𝜇 𝜎 (𝑦, 𝑦 ′) = (𝜎(𝑥 ∗ 𝑦) · 𝜎(𝑥 ′ ∗ 𝑦 ′)) · (𝜎(𝑦) · 𝜎(𝑦 ′)) = (𝜎(𝑥 ∗ 𝑦) · 𝜎(𝑦)) · (𝜎(𝑥 ′ ∗ 𝑦 ′) · 𝜎(𝑦 ′)) ≤ 𝜎 (𝑥) · 𝜎(𝑥 ′ ) = 𝜇 𝜎 (𝑥, 𝑥 ′ ). 𝐴𝑛𝑑, 𝜇 𝜎 (x, x ′ )· 𝜇 𝜎 (y, y ′) = (σ(x) · σ(x ′)) · (σ(y) · σ(y ′)) = (σ(x) · σ(y)) · (σ(x ′) · σ(y ′)) ≤ 𝜎 (𝑥 ∗ 𝑦) · 𝜎( 𝑥 ′ ∗ 𝑦 ′ ) = 𝜇 𝜎 (𝑥 ∗ 𝑦, 𝑥 ′ ∗ 𝑦 ′) = 𝜇 𝜎 ((𝑥, 𝑥 ′) ∗ (𝑦, 𝑦 ′)). Thus 𝜇 𝜎 is a fuzzy dot BH-ideal of X × X. Conversely suppose that 𝜇 𝜎 is a fuzzy dot BH-ideal of X × X. From (FBH1) we get (σ(0) )2 = σ (0) · σ(0)= 𝑐 (0, 0) And so σ (0) ≥ σ(x) for all x ∈ X. Also we have ( σ(x) )2 = µσ ((x, x ) ≥ µσ ((x, x)*(y, y)). µσ (y, y) =µσ ((x∗y ), (x ∗ y)). µσ (y, y) =((σ(x ∗ y) · σ(y)) )2 Which implies that 𝜎(𝑥) ≥ 𝜎(𝑥 ∗ y) · σ(y) for all x, y ∈ X. Also we have (𝜎(𝑥 ∗ 𝑦)2 =𝜇 𝜎 ((x∗y ), 𝑥 ∗ 𝑦) =𝜇 𝜎 ((𝑥, 𝑥) ∗ (𝑦, 𝑦)) ≥ µσ(𝑥, 𝑥). µσ(𝑦, 𝑦) = (σ(𝑥) · σ( 𝑦 ))2 So 𝜎(𝑥 ∗ 𝑦) ≥ 𝜎(𝑥) · 𝜎(𝑦) for all x, y ∈X. Therefore σ is a fuzzy dot BH-ideal of X. Proposition 4.15. Let μ be a left fuzzy relation on a fuzzy subset σ of a BH-algebra X. If μ is a fuzzy dot BH-ideal of X × X, then σ is a fuzzy dot BH-ideal of a BH-algebra X. Proof. Suppose that a left fuzzy relation μ on σ is a fuzzy dot BH-ideal of X × X. Then σ (0) = μ (0, z ) ∀z ∈ X By putting z=0 σ (0) = μ (0,0) ≥ μ (x , y )=σ (x ), For all x∈ X. For any x, x ′, y, y ′∈ X
  • 12. K. Anitha and Dr. N. Kandaraj http://www.iaeme.com/IJARET/index.asp 361 editor@iaeme.com σ(x) = µ(x, y) ≥ µ((x, y) ∗ (x′ , y′)). µ(x′, y′) = µ((x ∗ x′), (y ∗ y′)). µ(y, y′)) = σ(x ∗ x′). σ(x ′) Also σ(x ∗ x′).= µ(x ∗ x′ , y ∗ y′) = µ((x, y) ∗ (x′ , y′ )) ≥ µ(x, y). µ(x′ , y′ ) =σ(x). σ(𝑥′) Thus σ is a fuzzy dot BH-ideal of a BH-algebra X. REFERENCES [1] Y. Imai and K. Iseki, on axiom systems of propositional calculi XIV, Proc. Japan Acad 42 (1966), 19-22. [2] K. Iseki, An algebra related with a propositional calculus, Proc. Japan, Acad 42 (1966), 26-29. [3] Iseki K and Tanaka S: “An introduction to theory of BCK-algebras ”, Math. Japan. 23(1978), 1-26. [4] P. Bhattacharya and N. P. Mukherjee, Fuzzy relations and fuzzy groups, Inform. Sci. 36(1985), 267-282. [5] O. G. Xi, Fuzzy BCK-algebras, Math. Japan. 36(1991), 935-942. [6] L. A. Zadeh, Fuzzy sets, Information Control, 8(1965) 338-353. [7] K. Iseki and S. Tanaka, Ideal theory of BCK-algebras, Math. Japonica, 21(1976), 351-366. [8] A. Rosenfeld, Fuzzy groups, J. Math. Anal. Appl. 35 (1971), 512–517. [9] Y. B. Jun, E. H. Roh and H. S. Kim, On BH-algebras, Scientiae Mathematician 1(1) (1998), 347–354. [10] Q. Zhang, E. H. Roh and Y. B. Jun, on fuzzy BH-algebras, J. Huanggang Normal Univ. 21(3) (2001), 14–19. [11] J. Neggers and H. S. Kim, on d-algebras, Math. Slovaca, 49 (1996), 19-26. [12] M. Akram, on fuzzy d-algebras, Punjab University Journal of Math.37 (2005), 61-76.