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INTERSECTION-SOFT IDEALS IN CI-ALGEBRAS
INTERSECTION-SOFT IDEALS IN CI-ALGEBRAS
Journal of the Korean Society of Mathematical Education Series B The Pure and Applied Mathematics. 2014. Apr, 21(2): 105-112
Copyright © 2014, Korean Society of Mathematical Education
  • Received : November 14, 2013
  • Accepted : May 02, 2014
  • Published : April 27, 2014
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About the Authors
JUNG MI KO
DEPARTMENT OF MATHEMATICS, GANGNEUNG-WONJU NATIONAL UNIVERSITY, GANGNEUNG 210- 702, KOREAEmail address:jungmiko@gwnu.ac.kr
YONG CHAN KIM
DEPARTMENT OF MATHEMATICS, GANGNEUNG-WONJU NATIONAL UNIVERSITY, GANGNEUNG 210- 702, KOREAEmail address:yck@gwnu.ac.kr
SEOK ZUN SONG
DEPARTMENT OF MATHEMATICS, JEJU NATIONAL UNIVERSITY, JEJU 690-756, KOREAEmail address:szsong@jejunu.ac.kr

Abstract
The notion of intersection-soft ideal of CI -algebras is introduced, and related properties are investigated. A characterization of an intersection-soft ideal is provided, and a new intersection-soft ideal from the old one is established.
Keywords
1. INTRODUCTION
Mathematics requires that all mathematical notions (including set) must be exact, otherwise precise reasoning would be impossible. However, philosophers and recently computer scientists as well as other researcher have become interested in vague concepts [1 - 4 , 10 - 12] . One of them, Hájek [3] introduced a BL-algebra which is an algebraic structure for many valued logic. Many researchers investigated the various algebraic structures as MV-algebras, BCK-algebras, BE-algebras and CI-algebras [1 - 6 , 12] . As a generalization of a BCK-algebra, Kim and Kim [6] introduced the notion of a BE -algebra, and investigated several properties. The notion of CI -algebras is introduced by Meng [8] as a generalization of BE-algebras. Ideal theory and properties in CI -algebras are studied by Kim [5] .
On the hand, rough set theory was introduced by Pawlak [11 , 12] to generalize the classical set theory. Rough approximations are defined by the equivalence relation. There has been a rapid growth in interest in rough set theory in recent years. Its applications are decision system modeling and analysis of complex systems, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, business and finance, chemistry, computer engineering, environment, medicine, etc. As a generalization of a rough set, Molodtsov [9] introduced the concept of soft set as a new mathematical tool for dealing with uncertainties that is free from the di±culties that have troubled the usual theoretical approaches. Molodtsov pointed out several directions for the applications of soft sets. In [7] , Lee applied soft set theory to CI -algebras.
In this paper, we introduce the notion of int-soft ideal in CI -algebras, and investigate related properties. We provide a characterization of an int-soft ideal. We make a new int-soft ideal from the old one.
2. PRELIMINARIES
An algebra ( X ; *, 1) of type (2, 0) is called a CI - algebra if it satisfies the following properties:
  • (CI1)x*x= 1,
  • (CI2) 1 *x=x,
  • (CI3)x* (y*z) =y* (x*z),
for all x , y , z X . A CI -algebra ( X ; *, 1) is said to be transitive if it satisfies:
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A CI -algebra ( X ; *, 1) is said to be self-distributive if it satisfies:
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Note that every self-distributive CI -algebra is a transitive CI -algebra (see [5] ).
A non-empty subset I of a CI -algebra ( X ; *, 1) is called an ideal of X (see [5] ) if it satisfies:
  • (I1) (∀x,y∈X) (y∈I⇒x*y∈I),
  • (I2) (∀x,a,b∈X) (a,b∈I⇒ (a* (b*x)) *x∈I) .
Molodtsov [9] defined the soft set in the following way: Let U be an initial universe set and E be a set of parameters. Let P ( U ) denotes the power set of U and A E :
A pair(
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, A ) is called a soft set (see [9] ) over U , where
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is a mapping given by
In other words, a soft set over U is a parameterized family of subsets of the universe U . For ε∈ A ,
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(ε) may be considered as the set of ε-approximate elements of the soft set(
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, A). Clearly, a soft set is not a set. For illustration, Molodtsov considered several examples in [9] .
For a soft set (
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, X ) over U and a subset 𝛾 of U , the 𝛾- inclusive set of (
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, X ), denoted by (
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; 𝛾) , is defined to be the set
3. INTERSECTION-SOFT IDEALS
In what follows, denote by S( U , X ) the set of all soft sets of X over U where X is a CI -algebra unless otherwise specified.
Definition 3.1. A soft set (
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, X )∈ S ( U , X ) is called an intersection-soft ideal (briefiy, int-soft ideal ) (of X ) over U if it satisfies the following conditions:
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Example 3.2. Let X ={1, a , b , c , d , 0} be a CI -algebra with the following Cayley table:
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(1) Let (
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, X )∈ S ( U , X ) be given as follows:
where 𝛾 1 and 𝛾 2 are subsets of U with 𝛾 2 ⊈ 𝛾 1 . Then(
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, X ) is an int-soft ideal over U .
(2) For U =
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(the set of integers), let (
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, X ) ∈ S ( U , X ) be given as follows:
Then (
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, X ) is not an int-soft ideal over U since
Proposition 3.3. Every int-soft ideal (
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, X ) over U satisfies the following assertion :
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Proof . Using (CI2), (CI1) and (3.2), we have
for all x , y X . □
Lemma 3.4. Every int-soft ideal (
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, X ) over U satisfies the following assertion :
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Proof . Using (CI1) and (3.1), we have
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(1) =
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( x * x )⊇
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( x ) for all x X . □
Proposition 3.5. Every int-soft ideal (
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, X ) over U satisfies the following assertion :
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Proof . Taking y = 1 and z = y in (3.2) and using (CI2) and Lemma 3.4, we get
for all x , y X . □
Corollary 3.6. Every int-soft ideal(
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, X )over U satisfies the following assertion:
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Proof . Let x , y X be such that x * y = 1. Then
by (CI2) and (3.5). □
If a soft set (
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, X )∈ S ( U , X ) satisfies the condition (3.6), we say that(
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, X ) is order preserving . Hence every int-soft ideal is order preserving.
Proposition 3.7. If X is a transitive CI-algebra, then every int-soft ideal (
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, X ) over U satisfies the condition
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Proof . Let (
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, X ) be an int-soft ideal over U . Since X is transitive, we have
for all x , y , z X . It follows from (CI2), (3.2) and (3.5) that
  • (x*z)
  • =(1*(x*z))
  • =(((y*z)*z)*((x*(y*z))*(x*z))*(x*z))
  • ⊇((y*z)*z)∩(x*(y*z))
  • ⊇(x*(y*z))∩(y)
Therefore (3.7) is valid. □
Corollary 3.8. If X is a self-distributive CI-algebra , then every int-soft ideal (
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, X ) over U satisfies the condition (3.7).
Proposition 3.9. If a soft set (
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, X )∈ S ( U , X ) satisfies two conditions (3.4) and (3.7), then (
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, X ) is order preserving .
Proof . Let x , y X be such that x * y = 1. Then
by (CI1), (CI2), (3.7) and (3.4). Therefore (
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, X ) is order preserving. □
Theorem 3.10. If (
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, X ) is an int-soft ideal over U, then the set
is an ideal of X .
Proof . Let x X and a I . Then
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( a ) =
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(1), and so
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by (3.1). Combining this and (3.4), we have
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( x * a ) =
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(1), that is, x * a I . For any x , a , b X , if a , b I , then
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( a ) =
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(1) =
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( b ). It follows from (3.2) that
and so that
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(( a * ( b * x )) * x ) =
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(1): Thus ( a * ( b * x )) * x I . Therefore I is an ideal of X . □
We provide characterizations of an int-soft ideal.
Theorem 3.11. A soft set (
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, X )∈ S ( U , X ) is an int-soft ideal over U if and only if the 𝛾- inclusive set (
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; 𝛾) is an ideal of X for all 𝛾 ∈ P ( U ) with (
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; 𝛾) ≠ Ø.
The ideal (
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; 𝛾) in Theorem 3.11 is called the inclusive ideal of X .
Proof . Assume that(
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, X ) is an int-soft ideal over U . Let 𝛾 ∈ P ( U ) be such that (
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; 𝛾) ≠ Ø. Let x X and a ∈ (
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; 𝛾) . Then
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( a ) ⊇ 𝛾. It follows from (3.1) that
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( x * a ) ⊇
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( a ) ⊇ 𝛾. Hence x * a ∈ (
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; 𝛾) . Let x X and a , b ∈(
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; 𝛾) . Then
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( a ) ⊇ 𝛾 and
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( b ) ⊇ 𝛾. Using (3.2), we have
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(( a * ( b * x )) * x ) ⊇
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( a ) ⊇
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( b ) ⊇ 𝛾, and thus ( a * ( b * x )) * x 2 (
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; 𝛾) . Therefore (
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; 𝛾) is an ideal of X for all 𝛾 ∈ P ( U ) with (
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; 𝛾) ≠ Ø.
Conversely, suppose that (
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; 𝛾) is an ideal of X for all 𝛾 ∈ P ( U ) with (
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; 𝛾) ≠ Ø. For any a X , let
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( a ) = 𝛾. Then a ∈ (
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; 𝛾) . Since (
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; 𝛾) is an ideal of X , we have x * a ∈ (
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; 𝛾) for all x X . Thus
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( x * a ) ⊇ 𝛾 =
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( a ) for all x , a X . For any x , y X , let
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( x ) = 𝛾 x and
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( y ) = 𝛾y. Take 𝛾 = 𝛾 x ∩ 𝛾 y . Then x , y ∈ (
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; 𝛾) which implies that ( x * ( y * z )) * z ∈ (
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; 𝛾) for all z X . Hence
for all x , y , z X . Thus(
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, X ) is an int-soft ideal over U . □
Theorem 3.12. For any soft set (
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, X ) ∈ S ( U , X ), let (
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, X ) ∈ S( U , X ) be defined by
PPT Slide
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where 𝛾 and 𝛿 are subsets of U with 𝛿 ⊈
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( x ). If (
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, X ) is an int-soft ideal over U , then so is (
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, X ).
Proof. It is straightforward by Theorem 3.11. □
Theorem 3.13. Every ideal of X can be realized as an inclusive ideal of some int-soft ideal over X.
Proof . Let I be an ideal of X . Define a soft set(
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, X )∈ S ( U , X ) as follows:
PPT Slide
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where 𝛾 is a nonempty subset of U . Let x , y X . If y I , then x * y I and so
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( y ) = 𝛾 =
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( x * y ). If y =∉ I , then
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( y ) Ø ⊆
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( x * y ). For any x , a , b X , let a , b I . Then ( a * ( b * x )) * x I and thus
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( a )∩
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( b ) = 𝛾 =
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(( a * ( b * x )) * x ). If a =∉ I or b =∉ I , then
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( a ) Ø or
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( b ) Ø. Hence
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( a )∩
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( b ) Ø ⊆
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(( a * ( b * x )) * x ). Obviously, (
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; 𝛾) = I . This completes the proof. □
For any a , b X , consider the following set:
Theorem 3.14. Every int-soft ideal (
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, X ) over U satisfies the following assertion :
PPT Slide
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Proof. Assume that (
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, X ) is an int-soft ideal over U .Let a , b X be such that a , b ∈ (
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; 𝛾) . Then
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( a ) ⊇ 𝛾 and
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( b ) ⊇ 𝛾. If y C ( a , b ), then a * ( b * y ) = 1 and so
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by (CI2) and (3.2). Hence y ∈ (
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;𝛾) .Therefore C ( a , b ) ⊆(
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; 𝛾) . □
Corollary 3.15. For every int-soft ideal (
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, X )over U , we have
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Acknowledgements
This work was supported by the Research Institute of Natural Science of Gangneung-Wonju National University.
References
Bèlohlávek R 2002 Fuzzy Relational Systems Kluwer Academic Publishers New York
Bèlohlávek R 2004 Concept lattices and order in fuzzy logic Ann. Pure Appl. Logic 128 277 - 298    DOI : 10.1016/j.apal.2003.01.001
Hájek P 1998 Metamathematices of Fuzzy Logic Kluwer Academic Publishers Dordrecht
Hohle U , Klement E.P 1995 Non-classical logic and their applications to fuzzy subsets Kluwer Academic Publisher Boston
Kim K.H 2011 A note on CI-algebras Int. Math. Forum 6 (1) 1 - 5
Kim H.S , Kim Y.H 2007 On BE-algerbas Sci. Math. Jpn. 66 (1) 113 - 116
Lee K.J Int-soft filters in CI-algebras Far East J. Math. Sci. (FJMS)
Meng B.L 2010 CI-algebras Sci. Math. Jpn. 71 (1) 11 - 17
Molodtsov D 1999 Soft set theory - First results Comput. Math. Appl. 37 19 - 31
Pawlak Z 1982 Rough sets Int. J. Comput. Inf. Sci. 11 341 - 356    DOI : 10.1007/BF01001956
Pawlak Z 1984 Rough probability Bull. Pol. Acad. Sci. Math. 32 607 - 615
Turunen E 1999 Mathematics Behind Fuzzy Logic A Springer-Verlag Co.