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Research Articles

On some algebraic aspects of η-intuitionistic fuzzy subgroups

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Pages 463-469 | Received 31 Oct 2019, Accepted 12 Mar 2020, Published online: 31 Mar 2020

Abstract

In this study, we presents the idea of η-intuitionistic fuzzy subgroup (IFSG) defined on η-intuitionistic fuzzy set (IFS). Furthermore, we prove that every IFSG is an η-IFSG. Also, we extend the study of this notion to define η-intuitionistic fuzzy cosets and η-intuitionistic fuzzy normal subgroups of a given group and investigate some of their fundamental algebraic features. Besides, we define the η-intuitionistic fuzzy homomorphism between two η-IFSG’s and show that an η-intuitionistic fuzzy homomorphic image (inverse image) of the η-IFSG is an η-IFSG.

1. Introduction

The thought of a set and set hypothesis are compelling ideas in mathematics. However, the predominant idea of the fundamental set hypothesis, that a component may belong to a set or not be in a set makes it roughly difficult to speak to quite a bit of human correspondence. In a crisp set, we have a clear idea of whether an element exists in a set or not. Fuzzy sets enable components to be modestly in a set. Every component gives a level of enrolment in a set. This enrolment esteem can go from 0 to 1. If it just permits the outrageous participations estimations of 0 and 1, it would be equal to crisp sets. Fuzzy logic has been utilized as a part of different applications. Specifically, facial example: acknowledgment, ventilation systems, clothes washers and vacuum cleaners. The idea of intuitionistic fuzziness began by happenstance. The intuitionistic fuzzy set theory serves significantly in modern mathematics as it generalizes the fuzzy set. This particular theory is being applied in many disciplines, including medical diagnosis, vulnerability assessment of gas pipeline networks, travel time and neural network models. Zadeh [Citation1] proposed the idea of fuzzy sets in 1965. The most important motivation for studying the theory of intuitionistic fuzzy sets is the ability to deal with the uncertainty and vagueness of a physical problem much more effectively than with the theory of the classic fuzzy set, especially in the area of logic programming and decision-making, Financial services, psychological examinations, medical diagnosis, career determination and artificial intelligence. For instance, This logic enables to identify the type of course to be taken to obtain a certain type of job by developing suitable skills. In addition, this theory is also used to find the relationship between the different types of academic courses and the different types of skills that can be developed through the courses. The traffic problem is a wide human-oriented area with diverse and challenging tasks that need to be solved. Characteristics and performance of transport system services, costs, infrastructure, vehicles and control systems are usually determined on the basis of a quantitative assessment of their main effects. Most transportation decisions take place under inaccuracy, uncertainty and partial truth. Some lenses and boundary conditions are often difficult to measure against crisp values and in the context of classic fuzzy logic. The concept of the intuitionist fuzzy subgroup offers a useful technique for real life transportation problems. This special phenomenon is used to model the structure of the controling an intersection of two one-way streets. Fuzzy subgroups on fuzzy sets and their elemental consequences were studied by Rosenfeld [Citation2] in 1971. Das [Citation3] remodelled these concepts and proposed the definition of level subgroups in 1981. Mukherjee and Bhattacharyya [Citation4] explored the normality of a fuzzy subgroup and defined fuzzy cosets in 1984. The idea of fuzzy homomorphism and the related consequences of fuzzy subgroups was initiated by Choudhury et al. [Citation5] in 1988. Gupta and Qi [Citation6] extended these ideas and worked on t-norms accompanied by the fuzzy inference method in 1991. Ajmal and Prajapati [Citation7] analysed the concept of fuzzy cosets along with fuzzy normal subgroups in 1992. In 1998, Yaun and Zou [Citation8] investigated the equivalence relation on fuzzy subgroups. Mordeson et al. [Citation9] conversed about the nilpotency of fuzzy subgroups and many valuable algebraic features of fuzzy subgroups in 2005. Atanassov [Citation10] augmented the fuzzification of sets to commence the idea of Intuitionistic fuzzy sets in 1986. Biswas [Citation11] enhanced this notion by studying the intuitionistic fuzzification of subgroups and proposed some new definitions. Georgiev and Atanassov [Citation12] extended this idea of intuitionistic fuzzification and defined their logic operations in 1995. In 1998, Coker [Citation13] presented the idea of intuitionistic point. Atanassov [Citation14] discussed many important properties of the intuitionistic fuzzy set in 1999. Hur et al. [Citation15] introduced intuitionistic M-fuzzy groups in 2004. This idea was extended by Zhan and Tan [Citation16] to initiate the idea of multi M-fuzzy groups and some associated results in 2004. Palaniappan [Citation17] initiated the concept of intuitionistic L-fuzzy subgroup in 2009. In 2010, Marashdesh and Salleh [Citation18] utilized the idea of intuitionistic fuzzy space and commenced the study of intuitionistic fuzzy normal subgroups. Li and Wang [Citation19] investigated the (λ,α) homomorphism of fuzzy subgroups in 2011. Sharma [Citation20] defined (α,β)cut of intuitionistic fuzzy groups in 2011. He also defined the notions of t-intuitionistic fuzzy set and t-intuitionistic fuzzy subgroup in [Citation21]. Doda and Sharma [Citation22] studied the finite groups of different orders and gave the idea of recording the count of intuitionistic fuzzy subgroups in 2013. In [Citation23] the authors used interval-valued intuitionistic fuzzy values to set up a new multiple attribute decision making approach. Zeng et al. [Citation24] established a new technique of induced aggregation for intuitionistic fuzzy set. For more study on intuitionistic fuzzy sets, we recommend reading of [Citation25–34].

The major contributions of this paper are;

  1. The notion of η-IFSG over η-IFS has been introduced.

  2. A study to obtain a class of IFSG that correspond to a given IFSG has been proposed.

  3. The notions of η-intuitionistic fuzzy cosets and η-intuitionistic fuzzy normal subgroups have been defined and their various fundamental algebraic attributes have been established

  4. The study of this phenomenon has been extended by presenting the concept of η-intuitionistic fuzzy homomorphism between any two η-IFSG’s.

  5. The behaviour of an η-intuitionistic fuzzy homomorphic image of this particular homomorphism has been investigated.

The rest of the paper is organized as follows: The basic definitions of the intuitionistic fuzzy subgroup and the associated results have been presented in Section 2. In Section 3, we define η-intuitionistic fuzzy subgroups based on η-intuitionistic fuzzy sets and establishes many basic algebraic properties of this notion. Moreover, we use this idea to define η-intuitionistic fuzzy cosets and η-intuitionistic fuzzy normal subgroups and investigate many algebraic properties for these particular groups. The Section 4 extends the study of this phenomenon to introduce η-intuitionistic fuzzy homomorphism between two given η-IFSG’s and describes the effect of η-intuitionistic fuzzy homomorphism on these groups.

2. Preliminaries

This section is devoted to review some productive concepts of intuitionistic fuzzy group and related results that are mandatory to understand the subsequent study of this article.

Definition 2.1:

[Citation10] An intuitionistic fuzzy set (IFS) α is an augmentation of the classical fuzzy set which defines the degree of membership τα(s1) and non-membership ξα(s1), for every s1 in the universe S to the close unit interval. Each ordinary intuitionistic fuzzy set is given by α={<s1,τα(s1),ξα(s1)|s1S>}, 0τα(s1)+ξα(s1)1.

Definition 2.2:

[Citation11] An IFS α is called intuitionistic fuzzy subgroup (IFSG) if it admits the following conditions:

  1. τα(s1s2)min{τα(s1),τα(s2)},

  2. ξα(s1s2)max{ξα(s1),ξα(s2)},

  3. τα(s11)=τα(s1),

  4. ξα(s11)=ξα(s1), for all s1,s2G.

Definition 2.3:

[Citation20] Let γ and δ be positive real numbers lie in closed unit interval such that 0γ+δ1. The (γ,δ) – cut set of an IFS α of the universe S is a crisp set consisting of all those elements of S for which τα(s1)γ and ξα(s1)δ for all s1S.

Remark 2.4:

[Citation20] An IFS α of a group G is IFSG if each of its (γ,δ) – cut set is a subgroup of G.

Definition 2.5:

[Citation15] Let α be an IFSG of G and s1S. An IFS αs1 of G is called intuitionistic fuzzy right coset of α in G if (αs1)(g)=(ταs1(g),ξαs1(g)), where ταs1(g)=τα(gs11) and ξαs1(g)=ξα(gs11) for all gG.

The intuitionistic fuzzy left coset of αcan be defined in the similar manner.

Definition 2.6:

[Citation15] An IFS α is said to be intuitionistic fuzzy normal subgroup (IFNSG) if it meets the following conditions:

  1. τα(s1s2)=τα(s2s1)

  2. ξα(s1s2)=ξα(s2s1), for all s1,s2G.

Definition 2.7:

The averaging operator of two IFS’s α and β of the universe S, denoted by α$β, is defined as α$β=<s1,τα(s1)τβ(s1),ξα(s1)ξβ(s1)>:s1S.

3. Algebraic aspects of η-intuitionistic fuzzy subgroups

In this section, we study η-intuitionistic fuzzy subgroup. Moreover, numerous useful results and algebraic properties are introduced.

Definition 3.1:

Suppose α is an IFS of a universe S and η[0,1]. Then IFS αη=(ταη,ξαη) is called η-IFS of universe S with respect to IFS α, where, ταη(s1)=ψ{τα(s1),η},ξαη(s1)=ψ{ξα(s1),1η} and ψ,ψ denote the averaging operator defined in (2.7).

Next result demonstrates the essential attribute about the intersection of any two η-IFS’s of universe S.

Proposition 3.2:

The intersection of any two η-IFS’s is an η-IFS.

Proof:

Let αη and βη be two η-IFS’s of the universe S, then τ(αβ)η(s1)=ψ{τ(αβ)(s1),η}=ψ{min{τα(s1),τβ(s1)},η}=ψ[min{τα(s1),η},min{τβ(s1),η}]=min{ταη(s1),τβη(s1)}=ταηβη(s1),for alls1S.Similarly, it can be proved that ξ(αβ)η(s1)=ξαηβη(s1) for all s1S.

Hence (αβ)η=αηβη.

Remark 3.3:

The union of any two η-IFS’s is also η-IFS.

Definition 3.4:

An η-IFSG of group G is an η-IFS αη satisfying the following conditions:

  1. ταη(s1s2)min{ταη(s1),ταη(s2)}.

  2. ξαη(s1s2)max{ξαη(s1),ξαη(s2)}.

  3. ταη(s11)=ταη(s1).

  4. ξαη(s11)=ξαη(s1), for all s1,s2G.

Remark 3.5:

Let e be an identity element of G, then αη(s1)αη(e), s1G.

Also, αη(s1s21)=αη(e) implying that αη(s1)=αη(s2), for all s2G.

Proposition 3.6:

Every IFSG of G is an η-IFSG of G.

Proof:

Let s1,s2G, then by using the fact that α is an IFSG, we have ταη(s1s2)=ψ{τα(s1s2),η}ψ[min{τα(s1),τα(s2)},η]=ψ[min{τα(s1),η},min{τα(s2),η}]=min{ταη(s1),ταη(s2)}.Similarly, it can be proved that ξαη(s1s2)max{ξαη(s1),ξαη(s2)}.Moreover, ταη(s11)=ψ{τα(s11),η}=ψ{τα(s1),η}=ταη(s1).Similarly, ξαη(s11)=ξαη(s1).

Consequently, αη is an η-IFSG of a group G.

Remark 3.7:

An η-IFSG need not be an IFSG, that is, the converse of Proposition 3.6 does not hold.

The above algebraic fact can be viewed in the following example.

Example 3.8:

Let G={±1,±i} be the fourth root of unity. We define IFS α of G as α=<1,0.5,0.4>,<1,0.2,0.7>,<i,0.3,0.7>,<i,0.2,0.7>.Note that, αis not IFSG of G. Letη=0.4, then αη=<1,0.5,0.4>,<1,0.2,0.7>,<i,0.3,0.7>,<i,0.2,0.7>.It is clear that (0.5,0.4) – cut set of 0.4-IFS is α0.4={1} and α0.6={1}, whereas (0.3,0.7) – cut set of 0.4-IFS is given by α0.4={1,i} and α0.6={±1,±i}.

Note that, each of the above cut set of η-IFS is a subgroup of G. Hence it is an η-IFSG.

The following result presents the condition under which a given η-IFS is an η-IFSG.

Proposition 3.9:

Let α be any IFS of a group G such that τα(s11)=τα(s1) and ξα(s11)=ξα(s1) for all s1G. Moreover, η<min{l,1m}, where, l=min{τα(s1):s1G} and m=max{ξα(s1):s1G}, then α is an η-IFSG of G.

Proof:

In view of given conditions, we have l>η and m<1η. It follows that τα(s1)>η and ξα(s1)<1η, for all s1G. Therefore, ταη(s1s2)min{ταη(s1),ταη(s2)} and ξαη(s1s2)max{ξαη(s1),ξαη(s2)} for all s1,s2G. Moreover, for any s1G, we obtain

τα(s11)=τα(s1) and ξα(s11)=ξα(s1). This shows that ταη(s11)=ταη(s1) and ξαη(s11)=ξαη(s1).

The subsequent result indicates that the intersection of any two η-IFSG’s is an η-IFSG.

Proposition 3.10:

The intersection of two η-IFSG’s of a group G is also an η-IFSG of G.

Proof:

Suppose αη and βη are η-IFSG’s of G. Then τ(αβ)η(s1s2)=ψ{τ(αβ)(s1s2),η}=ψ{min{τα(s1s2),τβ(s1s2)},η}=ψ[min{τα(s1s2),η},min{τβ(s1s2)},η}]=min{ταη(s1s2),τβη(s1s2)}=ταηβη(s1s2)min[min{ταη(s1),ταη(s2)},min{τβη(s1),τβη(s2)}]=min[min{ταη(s1),τβη(s2)},min{ταη(s1),τβη(s2)}]=min{ταηβη(s1),ταηβη(s2)}.Similarly, it can be proved that for all s1,s2S ξ(αβ)η(s1s2)max{ξαηβη(s1),ξαηβη(s2)}.Also, τ(αβ)η(s11)=ψ{τ(αβ)(s11),η}=ψ[min{τα(s11),η},min{τβ(s11),η}]=min{ταη(s11),τβη(s11)}=min{ταη(s1),τβη(s1)}=ταηβη(s1).Similarly ξ(αβ)η(s11)=ξαηβη(s1).This concludes the proof.

Corollary 3.11:

The intersection of any number of η-IFSG’s of G is an η-IFSG of G.

Remark 3.12:

The union of two η-IFSG’s of group G may not be an η-IFSG of G.

Definition 3.13:

Let αη be an η-IFSG of G and s1G. An η-intuitionistic fuzzy right coset of α in G, denoted by αηs1, is defined as; αηs1(g)=(ταηs1(g),ξαηs1(g)), where, ταηs1(g)=ψ{τα(gs11),η} and ξαηs1(g)=ψ{ξα(gs11),1η} for all gG.

An η-intuitionistic fuzzy left coset of αη can be defined in a similar manner.

Definition 3.14:

An η-IFSG αη of G is called η-intuitionistic fuzzy normal subgroup (η-IFNSG) of G if s1αη=αηs1, for all s1G.

The following result shows that every IFNSG of G is also η-IFNSG of G.

Proposition 3.15:

If α is an IFNSG of a group G, then αη is also an η-IFNSG of G.

Proof:

Let α be an IFNSG of G, then for all s1,gG, τα(gs11)=τα(s11g) and ξα(gs11)=ξα(s11g),

implying that ταη(s11g)=ψ{τα(s11g),η}=ψ{τα(gs11),η}=ταη(gs11).Similarly, it can be proved that ξαη(s11g)=ξαη(gs11).

Consequently, s1αη=αηs1.

The converse of the given result doesn’t hold generally. This fact can be viewed in the successive example.

Example 3.16:

Consider the symmetric group of order 6, that is,

S3=p,q:p3=q2=e,qp=p2q. Define IFNSG α of S3 by τα(s1)=0.80ifs1∈<q>0.70otherwiseand ξα(s1)=0.10ifs1∈<q>0.13otherwise.then α=<e,0.80,0.10>,<p,0.70,0.13>,<p2,0.70,0.13>,<q,0.80,0.10>,<pq,0.70,0.13>,<p2q,0.80,0.13>.Since τα(s1s2)=0.700.80=τα(s2s1), therefore α is not an IFNSG.

Next, let η=0.1, then α0.1=<e,0.3,0.3>,<p,0.3,0.3>,<p2,0.3,0.3>,<q,0.3,0.3>,<pq,0.3,0.3>,<p2q,0.3,0.3>.One can see that α0.1 is an η-IFNSG.

In the following result, a condition for η-IFSG to be η-IFNSG is established.

Proposition 3.17:

Let αη be an η-IFSG of group G such that η<min{l,1m}, where l=ψ{τα(s1):s1G} and m=ψ{ξα(s1):s1G}, then αη is an η-IFNSG of G.

Proof:

Since l>η and m<1η, therefore min{τα(s1): s1G}>η and max{ξα(s1): s1G}<1η. Thus, τα(s1)>η, for all s1G.

Also, ξα(s1)<1η, so ταηs1(g)=ψ{τα(gs11),η}=θ and ξαηs1(g)=ψ{ξα(gs11),1η}=φ, for all gG.

Similarly, λsαη(g)=ψ{λα(s1g),η}=θ and ξs1αη(g)=ψ{ξα(s11g),1η}=φ.

This concludes the proof.

4. Some characterizations of η-intuitionistic fuzzy homomorphism

In this section, we define η-intuitionistic fuzzy homomorphism between any two η-IFSG’s and establish some important characterizations of this phenomenon.

Definition 4.1:

Let αη and βη be two η-IFSG’s of the groups G1 and G2 respectively and φ:G1G2 be a group homomorphism. Then φ is called η-intuitionistic fuzzy homomorphism from αη to βη if φ(αη)=βη.

The following result indicates that an η-intuitionistic fuzzy homomorphic image of the η-IFSG is an η-IFSG.

Theorem 4.2:

Let αη be an η-IFSG of group G1 and φ:G1G1 be a surjective homomorphism, then φ(αη) is an η-IFSG of group G2.

Proof:

In view of the given condition, for any two elements t1,t2G2, there exits s1,s2G1, such that φ(s1)=t1 and φ(s2)=t2.

Consider φ(αη)(t1t2)=(τφ(αη)(t1t2),ξφ(αη)(t1t2)). Then τφ(αη)(t1t2)=τ(φ(α))η(t1t2)=ψ{τφ(α)(φ(s1)φ(s2)),η}=ψ{τφ(α)(φ(s1s2)),η}ψ{τα(s1s2),η}=ταη(s1s2)min{ταη(s1),ταη(s2)}=min{τφ(αη)(t1),τφ(αη)(t2)}.Thus, τφ(αη)(t1t2)min{τφ(αη)(t1),τφ(αη)(t2)}.

Similarly, it can be proved that ξφ(αη)(t1t2)max{ξφ(αη)(t1),ξφ(αη)(t2)}.Further, τφ(αη)(t11)={ταη(s11):φ(s11)=t11}={ταη(s1):φ(s1)=t1}=τφ(αη)(t1).Similarly, ξφ(αη)(t11)=ξφ(αη)(t1).The following result illustrates that every η-intuitionistic fuzzy homomorphic image of the η-IFNSG is an η-IFNSG.

Theorem 4.3:

Let αη be an η-IFNSG of G1 and φ:G1G2 be a bijective homomorphism, then φ(αη) is an η-IFNSG of G2.

Proof:

In view of the given condition, for t1,t2G2, there exists a unique pair of elements s1,s2G1 such that φ(s1)=t1 and φ(s2)=t2.

Consider, (φ(α))η(t1t2)=(τ(φ(α))η(t1t2),ξ(φ(α))η(t1t2))which implies that τ(φ(α))η(t1t2)=ψ{τφ(α)(φ(s1)φ(s2)),η}=ψ{τφ(α)(φ(s1s2)),η}=ψ{τα(s1s2),η}which follows that ταη(s1s2)=ταη(s2s1)=ψ{τα(s2s1),η}=ψ{τφ(α)(φ(s2s1)),η}implies that ψ{τφ(α)(φ(s2)φ(s1)),η}=ψ{τφ(α)(t2t1),η}=τ(φ(α))η(t2t1).Similarly, one can prove that ξ(φ(α))η(t1t2)=ξ(φ(α))η(t2t1).The following result depicts that every η-intuitionistic fuzzy inverse homomorphic image of η-IFSG is always η-IFSG.

Theorem 4.4:

Let βη be an η-IFSG of a group G2 and φ be a group homomorphism from groups G1 to G2, then φ1(βη) is also an η-IFSG of G1.

Proof:

Suppose βη is an η-IFSG of G2, then there exists a unique pair of elements s1,s2G1 such that φ1(βη)(s1s2)=(τφ1(βη)(s1s2),ξφ1(βη)(s1s2)). Also, τφ1(βη)(s1s2)=τβη(φ(s1s2))=τβη(φ(s1)φ(s2))min{τβη(φ(s1)),τβη(φ(s2))}=min{τφ1(βη)(s1),τφ1(βη)(s2)}.Thus, τφ1(βη)(s1s2)min{τφ1(βη)(s1),τφ1(βη)(s2)}.

Similarly, one can prove that ξφ1(βη)(s1s2)max{ξφ1(βη)(s1),ξφ1(βη)(s2)}.

Moreover, τφ1(βη)(t11)=τ(βη)(φ(t11))=τ(βη)(φ(t1))1=τ(βη)(φ(t1))=τφ1(βη)(t1).Similarly, ξφ1(βη)(t11)=ξφ1(βη)(t1). Consequently, φ1(βη) is an η-IFSG of G1.

The following theorem, we prove that every η-intuitionistic fuzzy homomorphic inverse image of η-IFNSG is an η-IFNSG.

Theorem 4.5:

Let βη be an η-IFNSG of a group G2 and φ:G1G2 be a group homomorphism, then φ1(βη) is an η-IFNSG of G1.

Proof:

Suppose βη is an η-IFNSG of a group G2 then there exists a unique pair of elements s1,s2G1 such that φ1(βη)(s1s2)=(τφ1(βη)(s1s2),ξφ1(βη)(s1s2)), where τφ1(βη)(s1s2)=τβη(φ(s1s2))=τβη(φ(s1)φ(s2))=τβη(φ(s2)φ(s1))implying that τβη(φ(s2s1))=τφ1(βη)(s2s1).Similarly, one can prove that ξφ1(βη)(s1s2)=ξφ1(βη)(s2s1). Thus, φ1(βη) is an η-IFNSG of G1.

5. Conclusion

The η-intuitionistic fuzzy set generalizes the concept of classical fuzzy set intending to to assess the ambiguity level of a fuzzy situation. In this research, we have presented cosets and subgroups of η-intuitionistic fuzzy sets and then used these concepts to construct the η-intuitionistic fuzzy normal subgroup. After discussing some important features of these concepts, we demonstrated the effectiveness of the image and inverse image of η-intuitionistic fuzzy normal subgroup followed by η-intuitionistic fuzzy homomorphism.

Acknowlegements

This research project was supported by a grant from the Research Center of the Center for Female Scientific and Medical Colleges, Deanship of Scientific Research, King Saud University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research project was supported by a grant from the Research Center of the Center for Female Scientific and Medical Colleges, Deanship of Scientific Research, King Saud University.

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