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Pure Mathematics

Fuzzy ideals and fuzzy filters of bounded semihoops

ORCID Icon & | (Reviewing editor:)
Article: 2341484 | Received 17 Nov 2023, Accepted 07 Apr 2024, Published online: 26 Apr 2024

ABSTRACT

In this research paper, we present the concept of fuzzy ideals and fuzzy filters within bounded semihoops, examining their properties. We derive several characterizations for the smallest fuzzy ideals and filters containing a given fuzzy set. Furthermore, we analyze the properties and characterizations of prime fuzzy ideals, prime fuzzy filters, fuzzy primary ideals, and fuzzy primary filters. Lastly, we explore the fuzzy congruence relation associated with fuzzy (primary) ideals and fuzzy (primary) filters.

MATHEMATICS SUBJECT CLASSIFICATION:

1. Introduction

Hoops, introduced by Bosbach (Citation1969, Citation1970), are naturally ordered commutative residuated integral monoids. The class of basic hoop algebras, as established by Aglianó et al. (Citation2007), is a significant development within the realm of algebra. It has been proven that any variety of BL-algebras encompasses the variety of basic hoop algebras. Semihoops, a more general form of hoops, were introduced by Esteva et al. (Citation2003). A semihoop is a type of hoop that does not meet the divisibility requirement. It encompasses all algebraic structures that are induced by left-continuous t-norms, making it significant in fuzzy logics and related algebraic structures. The study of these algebras and the completeness of the correspondence logic system involves the important role of filter and ideal theory. The examination of ideals and filters on semihoops has been extensive, leading to interesting findings in (NiuIdeal et al., Citation2020) and (Borzooei & Aaly Kologani, Citation2015), respectively. Moreover, in these works, the definitions and characterizations of prime, primary, and perfect ideals (and filters) of semihoops were introduced.

The concept of fuzzy subsets, introduced by L. A. Zadeh as an extension of classical set theory in (Zadeh, Citation1965), revolutionized the way we perceive sets. A fuzzy subset of a set is mathematically defined by assigning a value within the unit interval [0,1] to each element in the universe of discourse, indicating its degree of membership. Fuzzy set theory offers methods to represent imprecision and uncertainty in situations lacking clear boundaries. This mathematical framework enables us to model imprecision and uncertainty inherent in phenomena with vague boundaries. Subsequently, extensive research on fuzzy sets has emerged, with numerous applications across different domains (see (Lu et al., Citation2023)).

Rosenfeld, in his seminal paper (Rosenfeld, Citation1971), has introduced the concept of fuzziness into group theory. This research has inspired scholars to reconsider various abstract algebra concepts and findings within the broader context of a fuzzy environment, providing motivation for further exploration. Recent studies have focused on exploring topics such as fuzzy ideals and fuzzy prime ideals in universal algebras (Alaba & Addis, Citation2019a, Citation2019b), expanding the application of fuzzy concepts. Furthermore, the extension of fuzzy ideals and filters in MS-algebras and distributive lattices has been the subject of investigation in a series of papers (Alaba & Alemayehu, Citation2019a, Citation2019b; Norahun, Citation2020), highlighting the growing interest in this area. Moreover, a fuzzy congruence relation within an algebraic structure is defined as a fuzzy equivalence relation compatible with all basic operations of the algebra. The study of fuzzy congruence relations has been extended to various algebraic structures, demonstrating the broad applicability of this concept. Notably, recent research has focused on this topic in different contexts: in Ockham algebras (see (Alemayehu et al., Citation2021, Citation2022)) and more broadly, in universal algebras (see (Addis, Citation2022)), showing the diverse applications of fuzzy congruence relations.

The study of fuzzification in algebraic structures remains an active field of mathematical research. In the existing literature, researchers have explored different aspects of fuzzy ideals and filters in universal algebras, distributive lattices, and MS-algebras, contributing to the advancement of understanding. The research conducted by these scholars has significantly advanced the understanding and application of fuzzy concepts in different algebraic structures and settings. It has been noted that many fundamental results in conventional algebraic structures also apply to fuzzified algebraic concepts, highlighting the relevance and significance of this research direction. The exploration of fuzzy ideals and fuzzy filters within bounded semihoops is motivated by the desire to extend traditional algebraic concepts into the realm of fuzzy algebra. By investigating these fuzzy structures in the context of bounded semihoops, we aim to enhance our understanding of how imprecision and uncertainty can be effectively modeled within algebraic systems. The concept of fuzzy ideals and fuzzy filters within bounded semihoops is a fascinating area of study in algebra.

Building upon the aforementioned studies, this paper delves into exploring fuzzy ideals and fuzzy filters within a bounded semihoop, examining their properties. Furthermore, it delves into characterizing fuzzy ideals and filters generated by a fuzzy subset. Additionally, it investigates prime fuzzy ideals and filters, fuzzy primary ideals and filters, along with their respective characterizations. Lastly, it explores the concept of fuzzy congruence relations associated with fuzzy (primary) ideals and fuzzy (primary) filters, contributing to the ongoing discourse in this evolving field.

The unit interval [0,1] is recognized for its numerous lattice theoretic and topological properties. Due to this, we opt to use the unit interval [0,1] as the set of truth degrees for our fuzzy statements throughout the paper. The paper is organized as follows. In Section 2, we gather the basic notions and results in fuzzy sets and bounded (semihoops). In Section 3 and Section 4, we introduce the notion of fuzzy ideals (respectively, filters) in bounded semihoop and investigate their properties. Also, characterizations of fuzzy ideals and fuzzy filters generated by a fuzzy subset are discussed. In Section 5, we explore the concept of fuzzy congruence relations associated with fuzzy (primary) ideals and fuzzy (primary) filters.

2. Preliminaries

In this topic, we start with basic definitions and important results in fuzzy set and semihoops which we need in the sequel.

Definition 2.1.

(Esteva et al., Citation2003)

An algebra (H,,$\break$,,1) of type (2,2,2,0) is called a semihoop if it satisfies the following conditions:

  1. (H,,1) is a semilattice with greatest element 1,

  2. (H,,1) is a commutative monoid,

  3. (st)u=s(tu), for all s,t,uH.

By a fuzzy subset ξ of a semihoop H, we mean a mapping ξ:H[0,1]. The set {ξ(s):sH} is called the image of ξ, and is denoted by Im(ξ). For each α[0,1], the set

ξ1([α,1])={sH:α  ξ(h)1}.

is called the α-level subset of ξ. For any fuzzy subset ξ of a semihoop H and each tH, we have

ξ(s)={α[0,1]:αξ1([α,1])}.

For any fuzzy subsets ξ and σ of a semihoop H, we write

ξσ to\ mean ξ(s)σ(s), for\ all sH

in the ordering of [0,1]. It can be easily verified that "" is a partial order on the set [0,1]H and is called the point wise ordering.

Given a semihoop (H,,,,1), the binary relation ≤ on H defined by: st if and only if st=1,∀s,tH is a partial ordering on H which we call the natural ordering on H and s1, for all sH. For any sH and nN{0}, where N is a set of natural number, define a power of s by:

sn={1ifn=0sn1sotherwise 

Theorem 2.2.

(Esteva et al., Citation2003)

Let (H,,,,1) be a semihoop. Then, the following properties are true for any s,t,uH:

  1. stu stu;

  2. sts,t;

  3. 1s=s,s1=1;

  4. sns,

  5. tst;

  6. if st, then tusu,usut and sutu;

  7. s(st)t;

  8. st(us)(ut),st(tu)(su);

  9. s(tu)=t(su).

A semihoop H is said to be bounded if there exists 0H such that 0s  sH. In a bounded semihoop H one can define the negation of each sH by s =s0. An element s in a bounded hoop H is defined to be closed if s=s, and H is said to have the double negation property (or DNP for short) provided that each of its element is closed; i.e. s=s, for all sH.

Theorem 2.3.

(Borzooei & Aaly Kologani, Citation2015)

If H is a bounded semihoop, then the following properties hold, for any s,tH:

  1. 1=0, 0=1;

  2. ss;

  3. ss =0;

  4. tts;

  5. st implies ts;

  6. stts;

  7. If H has a DNP, then st=ts.

Lemma 2.4.

(NiuIdeal et al., Citation2020)

Let H be a bounded semihoop . Then define a binary operation on H by:

st=st, for any s,tH.

Then the following properties hold for any s,t,uH:

  1. st, then sutu;

  2. sst;

  3. ss=1;

  4. 0s=s,s0=s;

  5. st=1st;

  6. (st)us(tu);

  7. if H has a DNP, then st =(st);

  8. if H has a DNP, then st=(st).

Note that if H is a bounded semihoop with DNP, then the binary operation is commutative and associative.

Theorem 2.5.

(Borzooei & Aaly Kologani, Citation2015)

Define a binary operation on a semihoop H by:

st=((st)t)((ts)s), for any s,tH.

Then the following conditions are equivalent:

  1. is associative;

  2. for all s,t,uH; stsutu;

  3. for all s,t,uH; s(ut) (st)(su);

  4. st is the supremum of s and t with respect to the natural ordering on H.

A semihoop H is called a -semi hoop, if it satisfies one of the equivalent conditions of the above theorem.

Definition 2.6.

(NiuIdeal et al., Citation2020)

Let H be a bounded semihoop. A non-empty subset I of H said to be an ideal of H, if it satisfies:

  1. st and tI imply sI, for any s,tH;

  2. stI, for any s,tI.

The set of all ideals of H will be denoted by I(H). If SH, then the intersection of all ideals of H containing S is denoted by (S] and is characterized by:

(S]={tH:∃nN and s1,,snS,tsn((s3(s2s1))}.

In particular, for any element sH we have

(s]={tH:tns for some nN},where ns=s((s(ss))

Definition 2.7.

(NiuIdeal et al., Citation2020)

A proper ideal I of a bounded semihoop H is called a primary ideal, if for all s,tH, stI implies either snI or tnI, for some positive integer n.

Definition 2.8.

(NiuIdeal et al., Citation2020)

Let H be a semihoop. A nonempty subset F is called a filter of H, if it satisfies the following conditions:

  1. stF, for all s,tF;

  2. for all s,tH, st and sF imply tF

Theorem 2.9.

(NiuIdeal et al., Citation2020)

A subset F of a semihoop H is said to be a filter of H if and only if the following conditions hold:

  1. 1F;

  2. s, stFtF, for all s,tH.

The set of all filters of H will be denoted by F(H). If SH, then the intersection of all filters of H containing S is denoted by [S) and is characterized by:

[S)={tH:∃nN and s1,,snS, s1snt}

In particular, for any element sH we have [s)={tH:snt,for\ some nN}.

Theorem 2.10.

(NiuIdeal et al., Citation2020)

A proper filter of K of a bounded semihoop H is called a primary filter, if for all s,tH, stK implies (sn)K or (tn)K, for some positive integer n .

3. Fuzzy ideals of on a bounded semihoops

In this section, we define fuzzy ideals in a bounded semihoop and investigate some of its properties. Throughout this paper, H stands for a bounded semihoop (H,,,,1) unless otherwise stated. We begin with the following.

Definition 3.1.

Let H be a bounded semihoop. Then, a fuzzy subset ξ of H is called the fuzzy ideal of ξ, if for all s,tH the following holds:

  1. ξ(0)=1;

  2. ξ(s)ξ(t)ξ(st);

  3. st implies ξ(t)ξ(s).

A fuzzy ideal ξ of H is called proper if  sH such that ξ(s)1.

FI(H) will represent the class of all fuzzy ideals of H. It is evident that the characteristic functions χ{0} and χH of {0} and H respectively, belongs to FI(H) and hence it is nonempty.

Example 3.2.

Let H={0,w,x,y,z,1} with 0<x, z<w<1, 0<y<c<1, where w and y are incomparable, x and z are incomparable. Define and on H as follows:

0wxyz10000000w0xxx0wx0xx00xy0z0xzyz000z0z10wxyz10wxyz10111111w0xxx0wx0xx00xy0z0xzyz000z0z10wxyz1

Then (H,,,,1) is a bounded semihoop, where st=s(st), for any s,tH. Define a fuzzy subsets ξ and λ on H by:
ξ(0)=1=ξ(x), ξ(w)=ξ(y)=ξ(z)=0.6, ξ(1)=0.2 and λ(0)=1, λ(y)=λ(z)=0.7, λ(w)=λ(x)=λ(1)=0.6.
Then it is routine to verify that ξ and λ are fuzzy ideals of H.

Theorem 3.3.

A fuzzy subset ξ of H is a fuzzy ideal of H if and only if ξ1([α,1]) is an ideal of H, for all α[0,1].

Proof.

Suppose that ξ is a fuzzy ideal of H and α[0,1]. Then α1=ξ(0) and so 0φ1([α,1]). Again let s,tφ1([α,1]). Then α  ξ(s) and α  ξ(t) This implies that α  ξ(s)ξ(t)  ξ(st) and hence stξ1([α,1]). Again let st and tφ1([α,1]). Then α  ξ(t)ξ(s) and so sξ1([α,1]). So ξ1([α,1]) is an ideal of H.

Conversely, suppose that ξ1([α,1]) is an ideal of H, for all α[0,1]. In particular, ξ1({1}) is an ideal. Since 0ξ1({1}), we have ξ(0)=1. Again let s,tH and put α=ξ(s)ξ(t). This implies that s,tξ1([α,1]) so we have stφ1([α,1]). Therefore ξ(s)ξ(t)=αξ(st). Again let s,tH such that st. Put β=ξ(t). Then tφ1([β,1]). Since φ1([β,1]) is an ideal of H and st, we have sξ1([β,1]). Therefore ξ(t)=βξ(s) and so ξ is a fuzzy ideal of H.

Corollary 3.3.1.

I is an ideal of H if and only if the characteristic function χI of I is a fuzzy ideal of H.

Theorem 3.4.

Let H be a bounded semihoop and ξ be a fuzzy subset of H. Then the following conditions are equivalent:

  1. ξ is a fuzzy ideal of H;

  2. ξ(0) =1, ξ(s)ξ(t) ξ(st) and ξ(st)ξ(s)ξ(t), for any s,tH;

  3. ξ(0) =1, ξ(s)ξ(t)ξ(st) and ξ((st))ξ(s)ξ(t), for any s,tH;

  4. ξ is normalized, ξ(s)ξ(t)ξ(st) and ξ(s)ξ(st), for any s,tH.

Proof.

(1) (2). Suppose that ξ is a fuzzy ideal of H. Then, by definition, ξ(0)=1. Let s,tH. Then ξ(s)ξ(t)ξ(st) and since t(s(st))=t(s(st)))=(ts) (ts)=1 we have t(s(st)) and hence

ξ(st)ξ(s)ξ(st)ξ(s)ξ(s(st))ξ(t).         (since t(s(st)))

Hence (2) holds.

(2) (3). Suppose that (2) holds. Let s,tH. Then since st(st)=(st), we have

ξ((st))ξ(s)ξ(st)ξ(s)ξ(t)           (by (2))ξ(t)           (since tt)

Hence (3) holds.

(3) (1). Suppose that (3) holds. Then ξ(0)=1 Again let s,tH such that st. Then ts. This implies that (ts) =(1) =0 and hence ξ((ts) =1. Thus ξ(t)=ξ(t)1=ξ(t)ξ((ts))ξ(s), by (3). Hence (3) (1) holds true.

(1) (4). It is clear.

(4) (1). Suppose that (4) holds. Since ξ is normalized, there exists uH such that ξ(u)=1. Now since 1=ξ(u)ξ(u0)=ξ(u(u0))=ξ(uu)=ξ(0), we have ξ(0)=1. Again let s,tH such that st. Then st=1. Now and ξ(t)ξ(ts)=ξ(st)=ξ(s(st))=ξ(s1)=ξ(s). Hence (1) holds.

Corollary 3.4.1.

Let ξ is a fuzzy ideal of H and sH. Then ξ(s)=1 if and only if ξ(s)=1.

Proof.

Suppose that ξ(s)=1. Since ss we have ξ((ss))=ξ(1)=ξ(0)=1. Now, by Theorem 3.4(3), 1=ξ((ss))ξ(s)ξ(s), we have ξ(s)=1. Conversely, suppose ξ(s)=1. Since ss, we have 1=ξ(s)ξ(s) and hence ξ(s)=1.

Theorem 3.5.

If {ξi:iΩ} is a class of fuzzy ideals of H, then iΩξi is a fuzzy ideal of H.

From Theorem 3.5, it can be easily observed that the class FI(H) of all fuzzy ideals of H is closed under arbitrary intersection. It follows from this fact that for any fuzzy subset φ in H, we can find the smallest fuzzy ideal of H containing φ which we call the fuzzy ideal of H generated by φ and will be denoted by (φ]. The following theorems give characterization for (φ] in different context.

In the following theorem, we characterize fuzzy ideals of H generated by a fuzzy subset in terms of ideals generated by its level subset.

Theorem 3.6.

For any fuzzy subset φ in H and any sH:

(φ](s)={α[0,1]:s(φ1([α,1])]}

Proof.

Let us put ξ to be a fuzzy subset of H given by:

ξ(s)={α[0,1]:s(φ1([α,1])]}

We claim that ξ is the smallest fuzzy ideal of H containing φ. Let us first show that ξ^ is an L-filter. Clearly ξ(0)=1. Let s,tH. Then

ξ(s)ξ(t)={α[0,1]:s(φ1([α,1])]}{β[0,1]:t(φ1([β,1])]}={αβ:s(φ1([α,1])],t(φ1([β,1])]}

If we put γ=αβ, then we get (φ1([α,1])](φ1([γ,1])] and (φ1([β,1])](φ1([γ,1])] So that s,t(φ1([γ,1])]. Now it follows from the above equality that;

ξ(s)ξ(t)={αβ:s(φ1([α,1])],t(φ1([β,1])]}{γ[0,1]:st(φ1([γ,1])]=ξ(st)

Let s,tH such that st. Now

ξ(t)={α[0,1]:t(φ1([α,1])]}{α[0,1]:s(φ1([γ,1])]=ξ(s)

Therefore ξ is a fuzzy ideal of H. It is also clear to see that φξ. Suppose that σ is any other fuzzy ideal of H such that φσ. Then it is clear that (φ1([α,1]]σ1([α,1]), for all α[0,1]. Now for any sH consider:

ξ(s)={α[0,1]:s(φ1([α,1]]}{α[0,1]:s(σ1([α,1]]}{α[0,1]:sσ1([α,1)}=σ(s).

Therefore ξ is the smallest fuzzy ideal containing φ, that is, ξ=(φ].

Theorem 3.7.

Let S be any subset of H. Then the (χS]=χ(S].

Proof.

Since (S] is an ideal of H, by Corollary 3.3.1, we have χ(S] is a fuzzy ideal of H. Again since S(S], we have χSχ(S]. Let ξ be any fuzzy ideal of H such that χSξ. Now we claim that χ(S]ξ. Let sH. If h(S], then χ(S](s)=0ξ(s). Let s(S]. Since χSξ, we have Sξ1({1}) (1-level subset of ξ). This implies that (S](ξ1({1}]=ξ1({1}). Thus sξ1 and hence ξ(s)=1. Therefore χ(S](s)=1=ξ(s). So that χ(S](s)ξ(s), for all sH. Hence the claim holds. Therefore χ(S] is the smallest fuzzy ideal of H containing χS and hence (χS]=χ(S].

The following is also another algebraic characterization of fuzzy ideals generated by a fuzzy subset of H.

Theorem 3.8.

Let φ be a fuzzy subset of H. Then, the fuzzy subset φ defined by: φ(0)=1 and for t ≠ 0,

φ(t)={i=1nφ(si):tsn((s3(s2s1))),s1,,snH}

is the fuzzy ideal of H generated by φ.

Proof.

Let 0tH and put

Pt={i=1nφ(si):tsn((s3(s2s1))),siH}  and  Qt={α[0,1]:s(φ1([α,1])]}.

Then, by Theorem 3.6, it is enough to show that Pt=Qt. Let αPt. Then α=i=1nφ(si) for some s1,,snH such that tsn((s3(s2s1))). This implies that αφ(si), for all 1in and so siφ1([α,1])(φ1([α,1])]. Since (φ1([α,1])] is an ideal, we have sn((s3(s2s1)))(φ1([α,1])] and as tsn((s3(s2s1)))(φ1([α,1])] we have t(φ1([α,1])], i.e. αQt. Hence PtQt. and so PtQt. Again let βQt. Then t((φ1([β,1])]. Then tsn((s3(s2s1)) for some s1,,snφ1([β,1]). This implies that βi=1nφ(si). Put α=i=1nφ(si). Then since tsn((s3(s2s1)), we have αPt. Thus for each βQt, we get αPt such that βα. So QtPt. Hence Pt=Qt. Therefore φ=(φ].

Definition 3.9.

Let H be a bounded semihoop with DNP. The proper fuzzy ideal λ of H is called a prime fuzzy ideal of H, if for any fuzzy ideals ξ and ν of H,

ξνλ implies\ either ξλ or νλ.

Lemma 3.10.

Let I be an ideal of H and α[0,1). Then the fuzzy subset Iα1 of H defined by:

Iα1(s)={1ifsIαifsI ,

for all sH is a fuzzy ideal of H.

In the following we characterize prime fuzzy ideal of H in terms of prime ideals of H and an element in [0,1).

Theorem 3.11.

Let H be a bounded -semihoop with DNP, P be an ideal of H and 1α[0,1]. Then Pα1 is a prime fuzzy ideal of H if and only if P is a prime ideal of H.

Proof.

Suppose that Pα1 is a prime fuzzy ideal of H. Now we show that P is a prime ideal of H. Since Pα1 is proper, we have PH. . Let R and S be ideals of H such that RSP. Then (SR)α1Pα1. Now since Rα1Sα1=(RS)α1Pα1 and Pα1 is a prime fuzzy ideal of H, we have either Rα1Pα1 or Sα1Pα1. This implies that either RP or SP. Thus P is a prime ideal of H.

Conversely, suppose that P is a prime ideal of H and α[0,1). Clearly, Pα1 is a proper fuzzy ideal of H. Now we show that Pα1 is prime L-fuzzy prime ideal. Suppose not. Then there exist fuzzy ideals ξ and ν of H such that

ξνPα1 and ξPα1 and νPα1.

Then there exist s,tH such that

ξ(s) > Pα1(s) and ν(t) > Pα1(t).

This implies that Pα1(s)=Pα1(t)=α and so sP and tP. Since P is a prime ideal of a bounded -semihoop with DNP, we have stP and so Pα1(st)=α. Now we have

(ξν)(st)=ξ(st)ν(st)  ξ(s)ν(t)>αα=α=αP(st),

which contradicts our assumption ξνPα1. Hence Pα1 is a prime fuzzy ideal of H.

Theorem 3.12.

Let ξ be a fuzzy ideal of H, where H is a bounded -semihoop with DNP. Then ξ is a prime fuzzy ideal of H if and only if there exist prime ideal of P of H such that ξ=Pα1, where α[0,1).

Proof.

Let H be a bounded -semihoop with DNP. Suppose that ξ is a prime fuzzy ideal of H. Since ξ is proper it assumes at least two values. Since ξ(0)=1, 1 is necessarily in Im(ξ). Suppose that α,βIm(ξ) other than 1. Then there exist s,tH such that ξ(s)=α and ξ(t)=β. Now we claim that α=β. Now put P=ξ1={uH:ξ(u)=1}. Consider the fuzzy ideals χ(s] and Pα1. Now we claim to show that χ(s]Pα1ξ. For any uH, if u(s], then it is clear that (χ(a]Pα1)(u)ξ(u). Let u(s]. Now, in this case, if uP, we have

(χ(s]Pα1)(u)=χ(s](u)Pα1(u)=1=ξ(u).

and if uP, then we have

(χ(s]Pα1)(u)=χ(s](u)Pα1(u)=1α=α=ξ(s)ξ(u).

Therefore in either cases, we have (χ(s]Pα1)(u)ξ(u), for all uH and so

χ(s]Pα1ξ.

But as ξ is a prime fuzzy ideal of H, we have

χ(a]ξ or Pα1ξ

But as χ(s](s)=1>α=ξ(s), we have χ(s]ξ. Therefore Pα1ξ. In particular, since tP, we get that α=Pα1(t)ξ(t)=β. In similar fashion, we can show that βα and hence α=β. So ξ assumes exactly one value say α other than 1 and hence μ=Pα1.

Again to show P is a prime ideal, let R,S be ideals of H such that RSP. Then since RSPχRχS=χRSχPPα1=ξ and ξ is a prime fuzzy ideal, we have either

χRξ=Pα1 or χSξ=Pα1

This implies that RP or SP. and hence either P is a prime ideal of H. The converse part of this theorem follows from the Theorem 3.11.

Theorem 3.13.

Let H be H is a bounded -semihoop with DNP. Then if ξ is a prime fuzzyy ideal of H, then ξ(st)=ξ(s) or ξ(t), for all s,tH.

Proof.

Suppose that ξ is a prime ideal of H. Then ξ=Pα1 for some prime ideal P of H and α[0,1). Let s,tH. If sP or tP, then stP and so ξ(st)=1=ξ(s) or ξ(t). If sP and tP, then xyI as a prime ideal and so ξ(st)=α=ξ(s)=ξ(t). Hence in either cases, we have ξ(st)=ξ(s) or ξ(t)

Theorem 3.14.

Let H be a bounded semihoop and s2=s, for any sH. If ξ fuzzy primary ideal of H, then ξ(st)=ξ(s)ξ(t), for all s,tH.

Proof.

Suppose that ξ a fuzzy primary ideal of H. Let s,tH. Then, since stst, we have ξ(st)ξ(st). Again since ξ is fuzzy primary ideal, there exists nN such that ξ(st)ξ(sn)ξ(tn). Since s2=s, for all sH, we get sn=s and tn=t. Therefore ξ(st)ξ(s)ξ(t).

Definition 3.15.

A proper fuzzy ideal ξ of H. is called a fuzzy primary ideal, if for all s,tH:

ξ(st)ξ(sn)ξ(tn), for some nN.

Example 3.16.

In Example 3.2, λ is a primary fuzzy ideal of H.

Theorem 3.17.

A fuzzy subset ξ of H is a fuzzy primary ideal of H if and only if ξ1([α,1]) is a primary ideal of H, for all α[0,1].

Corollary 3.17.1.

I is a primary ideal of H if and only if χI is a fuzzy primary ideal.

4. Fuzzy filters of bounded semihoops

In this section, we define a fuzzy filter in a bounded Semihoop and investigate some of its properties.

Definition 4.1.

A fuzzy subset ζ of H is called a fuzzy filter of H, if for all s,tH,

  1. ζ(1)=1;

  2. ζ(s)ζ(t)ζ(st);

  3. ζ(s)ζ(t), whenever st.

FF(H) will represent the class of all fuzzy filters of H. It is evident that the characteristic functions χ{1} and χH of {1} and H respectively, belongs to FF(H) and hence it is nonempty. The set of all filters of H is denoted by F(H).

Example 4.2.

Let H={0,s,t,1} be a chain. Define binary operations and on H by the following tables:

0st100000s00sst0stt10st10st101111ss111t0s1110st1

Then (H,,,,1) is a bounded semihoop, where st=min{s,t}, for every s,tH. Define a fuzzy subset of ζ on H by: ζ(0)=0.4=ζ(s),ζ(1)=ζ(t)=1. Then ζ is a fuzzy filter of H.

Theorem 4.3.

ζFF(H) if and only if ζ1([α,1])FF(H), for all α[0,1].

Corollary 4.3.1.

FF(H) if and only if χ{F}FF(H).

Theorem 4.4.

A fuzzy subset ζ of H is a fuzzy filter if and only if it satisfies the following conditions:

  1. ζ(1)=1;

  2. ζ(s)ζ(st)ζ(t), for every s,tH.

Proof.

Suppose that ζ is a fuzzy filter of H. Then, by definition, ζ(1)=1. Let s,tH. Then, since (s(st))t, we have ζ(s)ζ(st)ζ(s(st)) ζ(t).

Conversely suppose that ζ is a fuzzy subset of H satisfying the given condition. Then by (1), ζ(1)=1. Let s,tH. Now

ζ(s)ζ(t)=ζ(s)ζ(t)1=ζ(s)ζ(t)ζ(t(s(st)))(since  t(s(st))=1)ζ(s)ζ(s(st))ζ(st).

Again let s,tH such that st. Then st=1. Now ζ(s)=ζ(s)1=ζ(s)ζ(st)ζ(t). Therefore ζ is a fuzzy filter of H.

Theorem 4.5.

Let ζFF(H),SH and sH. Then the following conditions hold:

  1. t[s) ζ(s)ζ(t);

  2. If t[S), then there exist s1,,snS such that i=1nζ(si) ζ(t).

Proof.

(1) Let t[s). Then snt, for some nN and so ζ(s)=ζ(s)ζ(s)φ(sn)φ(t);

(2) Let SH and t[S), then s1,,snS such that s1snt and so ζ(s1)ζ(sn)ζ(s1sn)ζ(t)

Theorem 4.6.

ζFF(H) if and only if for any finite subset S of H, sSζ(s)ζ(t), for\ all t[S).

Proof.

Suppose that ζFF(H) and S is a finite subset of H. Put α=sSζ(s). Then αζ(s), for all sS and hence Sζ1([α,1]), the α-level subset of ζ. By Theorem 4.3, ζ1([α,1]) is a filter of H containing S. Therefore [S)ζ1([α,1]) and hence αζ(t), for all t[S). That is,

sSζ(s)ζ(t), for\ all t[S).

Conversely suppose that φ satisfies the given conditions. Now, since [)={1}, by hypothesis, we have 1=sζ(s)ζ(1) and hence ζ(1)=1. Let s,tH. Put S={s,st}. Then since s(st)t, we have t[S) and hence ζ(s)ζ(st)=sSζ(s)ζ(t). Therefore, by Theorem 4.4, ζ is a fuzzy filter of H.

Theorem 4.7.

If {ζi:iΩ} is a class of fuzzy filters of H, then iΩζi is a fuzzy filter of H.

From Theorem 4.7, it can be easily checked that the class FF(H) of all fuzzy filters of H is closed under arbitrary intersection. It follows from this fact that for any fuzzy subset ζ in H, we can find the smallest fuzzy filter of H containing ζ which we call the fuzzy filter of H generated by ζ and will be denoted by [ζ). It can be easily checked that the class FF(H) of all fuzzy filters of H is closed under arbitrary intersection. It follows from this fact that for any fuzzy subset ζ in H, we can find the smallest fuzzy filter of H containing ζ which we call the fuzzy filter of H generated by ζ and will be denoted by [ζ).

Now we give a characterization of any fuzzy filter generated by a fuzzy subset of H in terms of filters generated by its level subset.

Theorem 4.8.

For any fuzzy subset ζ of H, then the fuzzy subset given by:

[ζ)(s)={α[0,1]:s[ζ1([α,1])}, for\ all sH.

is a fuzzy filter of H generated by ζ, where [ζ1([α,1]) is a filter generated by the set ζ1([α,1]).

Theorem 4.9.

Let B be any subset of H. Then [χB)=χ[B).

In the following we give an algebraic characterization of fuzzy filter of H generated by a fuzzy subset of H.

Theorem 4.10.

Let ζ be a fuzzy subset of H. Then, the fuzzy subset ζ defined by: ζ(0)=1 and for t ≠ 0,

ζ(t)={i=1nφ(si):s1,,snS, s1snt}

is the fuzzy filter of H generated by ζ.

Definition 4.11.

Let H be a bounded semihoop with DNP. Then a proper fuzzy filter ζ of H is called a prime fuzzy ideal of H, if for any fuzzy filters τ,ρFF(H),

τρζ implies\ either τζ or ρζ.

Lemma 4.12.

Let F be a filter of H and α[0,1). Then the fuzzy subset Fα1 of H defined by:

Fα1(s)={1ifsFαifsF ,   for all sH is a fuzzy filter of H.

In the following we characterize prime fuzzy filter in a bounded -semihoop with DNP H in terms of prime filters of H and elements in [0,1).

Theorem 4.13.

Let ζ be a fuzzy filter of H, where H is a bounded -semihoop with DNP. Then ζ is a prime fuzzy filter of H if and only if there exist prime filter Q of H such that ζ=Qα1, where α[0,1).

Theorem 4.14.

Let H be a bounded -semihoop with DNP. Then if ζ is a prime fuzzyy filter of H, then ζ(st)=ζ(s) or ζ(t), for all s,tH.

Definition 4.15.

Let ζ be a proper fuzzy filter of a semihoop H. ζ is called a fuzzy primary filter, if for every s,tH, ζ((st)) ζ((sn))ζ((tn)), for some positive integer n.

Example 4.16.

In Example 4.2, ζ is a fuzzy primary filter.

Theorem 4.17.

A fuzzy subset ζ of H is a fuzzy primary filters of H if and only if ζ1([α,1]) is a primary filter of H, for all α[0,1].

Theorem 4.18.

Let H be a bounded -semihoop with (DNP), and u2=u, for every uH. If ζ is a fuzzy primary filter of H, then ζ(st)=ζ(s)ζ(t), for all s,tH.

5. Fuzzy congruences relation on semihoops

In this section we define the notion of fuzzy congruence relation in bounded semihoops and study their relation with fuzzy ideals (filters). By a fuzzy relation on H, we mean a fuzzy subset of H × H. For any α[0,1] and a fuzzy relation Φ on H, the set Φ1([α,1]={(s,t)H×H:αΦ(s,t)1} is called the α-level relation of Φ on H.

Definition 5.1.

A fuzzy relation Φ on H is called a fuzzy equivalence relation on H if

  1. Φ(s,s)=1 (reflexive),

  2. Φ(s,t)=Φ(t,s) for all s,tH (symmetric),

  3. Φ(s,t)Φ(t,u)Φ(s,u) for all s,t,uH (transitive).

Definition 5.2.

Let A={,,}. Then a fuzzy relation Φ on H is said to be compatible, if

Φ(s,t)Φ(u,v)Φ(su,tv) for all s,t,u,vH. and for all A.

Definition 5.3.

A compatible fuzzy equivalence relation on H is called a fuzzy congruence relation on H.

The class of all fuzzy congruence relations on H is denoted by FCon(H) and it is clear that FCon(H) is a complete lattice. For any sH and ΦFCon(H), define a fuzzy subset [s]Φ of H by:

[sΦ](t)=Φ(s,t), for all tH.

We call [s]Φ a fuzzy congruence class of Φ determined by s. Let us put

H/Φ={[s]Φ:sH}

Define binary operations , and on H/Φ by:

[h]Φ[g]Φ=[hg]Φ,[h]Φ[g]Φ=[hg]Φ and [h]Φ[g]Φ=[hg]Φ

Then it is routine to verify that (H/Φ,,,,[0]Φ,[1]Φ) is a bounded semihoop algebra and it is called the quotient bounded semihoop algebra of H modulo Φ.

For any fuzzy subset ξ of H, let us define a fuzzy relation Φξ on H as follows:

Φξ(s,t)=ξ((st))ξ((ts)), for all s,tH.

Theorem 5.4.

If ξ be a fuzzy ideal of H, then the fuzzy relation Φξ defined above is a fuzzy congruence relation of H.

Proof.

It is easy to check that Φξ is a fuzzy equivalence relation on H. Since st(su)(tu), for any uH, we have ((su)(tu))(st). Thus, as ξ is a fuzzy ideal, we have ξ((st))ξ(((su)(tu))). Similarly we have ξ((ts))ξ(((tu)(su))).

Φξ(s,t)=ξ((st))ξ((ts))ξ(((su)(tu)))ξ(((tu)(su)))=Φξ(su,tu)

Similarly, we can show that Φξ(s,t) Φξ(su,tu) and Φξ(s,t)Φξ(su,tu). Therefore, Φξ is a fuzzy congruence of H.

Define a binary operation on H/Φξ by:

[s]Φξ[t]Φξ if and only if ξ((st))=1, for all [s]Φξ,[t]ΦξH/Φξ.

Then it can and it can be easily verified that is a partial order and (H/Φξ,,,,[0]Φξ,[1]Φξ) is a bounded semihoop.

Theorem 5.5.

A proper fuzzy ideal ξ of H is a fuzzy primary ideal if and only if for any [s]Φξ,[t]ΦξH/Φξ, [s]Φξ[t]Φξ=[0]Φξ implies ([s]Φξ)n=[0]Φξ or ([t]Φξ)n=[0]Φξ, for some nN.

Proof.

Suppose that ξ is a fuzzy primary ideal of H and [s]Φξ[t]Φξ=[0]Φξ. Then [st]Φξ=[0]Φξ. This implies that ξ((st) 0))=1. That is, ξ((st))=1. Thus, by Corollary 3.4.1, we have ξ(st)=1. Thus since ξ(st)ξ(sn)ξ(tn), for some nN, we have ξ(sn)=1 or ξ(tn)=1. Then, by Corollary 3.4.1, we have ξ((sn))=1 or ξ((tn)))=1. If ξ((sn))=1, then ξ((sn0))=ξ((sn))=1 and hence [sn]Φξ[0]Φξ. Again since ξ((0sn))=ξ(1)=ξ(0)=1, we have [0]Φξ[sn]Φξ. Thus if ξ((sn))=1, we get ([s]Φξ)n=[0]Φξ. If ξ((tn))=1, by similar way we can show that ([t]Φξ)n=[0]Φξ.

Conversely suppose that ξ is a proper fuzzy ideal satisfying the given condition. Let ξ((st))=1, for some s,tH. Then, by Corollary 3.4.1, we have ξ((st))=1. Now, since ξ(((st) 0))=ξ((st))=1, we have [s]Φξ[t]Φξ=[st]Φξ[0]Φξ. Again, since ξ((0(st)))=ξ(1)\allowbreak=ξ(0)=1, we have [0]Φξ[st]Φξ=[s]Φξ[t]Φξ. Thus [s]Φξ[t]Φξ=[0]Φξ. Thus, by hypothesis, there exists nN such that ([s]Φξ)n=[0]Φξ or ([t]Φξ)n=[0]Φξ. If ([s]Φξ)n=[0]Φξ, then 1=ξ((sn0))=ξ((sn))=ξ(sn). By similar way, we can prove that ξ(tn)=1 Therefore, in any case, we have ξ(st)ξ(sn)ξ(tn), for some nN.. Therefore, ξ is a fuzzy primary ideal.

Now we discuss fuzzy congruence relation related to fuzzy (primary) filters. Let ζ is a fuzzy filter of a semihoop H. We define a fuzzy binary relation Ψζ on H by:

Ψζ(s,t)=ζ(st)ζ(ts), for all s,tH.

Then Ψζ is a fuzzy congruence relation on H.

Let H/Ψζ={[sΦζ]:sH}, where sΦζ is a fuzzy subset of H defined by : sΦζ(t)=Φζ(s,t), for\ all sH. Then the binary relation ”≤” on H/Ψζ which is defined by:

sΦζtΦζ if\ and\ only\ if ζ(st)=1,

is an order relation on H/Ψζ. Now, (H/Ψζ,,$\break$,,[1]Ψζ) is a semihoop, where for any s,tH:

[h]Ψζ[g]Ψζ=[hg]Ψζ,[h]Ψζ[g]Ψζ=[hg]Ψζ and [h]Ψζ[g]Ψζ=[hg]Ψζ

Theorem 5.6.

Let ζ be a proper fuzzy filter of H. Then ζ is a fuzzy primary filter if and only if [s]Ψζ[t]Ψζ=[0]Ψζ implies that there exists a natural number n such that ([s]Φζ)n=[0]Φζ or ([t]Φζ)n=0Φζ, for every sΦζ,tΦζH/Ψζ.

Proof.

Suppose that ζ is a fuzzy primary filter of a semihoop H and [s]Ψζ[t]Ψζ=[0]Ψζ. Then [st]Ψζ=[0]Ψζ. This implies that ζ((st) 0)=1. That is, ζ((st))=1. Thus, as ζ is a fuzzy primary filter, we have 1=ζ((st)) ζ((sn))ζ((tn)), for some positive integer n. If ζ((sn))=1, then ζ((sn0)=1 and hence ([s]Φζ)n[0]Φζ. Again since ζ((0sn))=ζ(1)=1, we have [0]Φζ([s]Φζ)n. Therefore ([s]Φζ)n=[0]Φζ. By similar way, if ζ((tn))=1, we have, ([t]Φζ)n=[0]Φζ.

Conversely suppose that ζ is a proper fuzzy filter satisfying the given condition. Let ζ((st))=1, for some s,tH. Then ζ((st) 0)=1 and hence [s]Ψζ[t]Ψζ=[st]Ψζ[0]Ψζ. Again, since ζ((0(st))=ζ(1)=1, we have [0]Ψζ[st]Ψζ=[s]Ψζ[t]Ψζ. Thus [s]Ψζ[t]Ψζ=[0]Ψζ. Thus, by hypothesis, there exists nN such that ([s]Ψζ)n=[0]Ψζ or ([t]Ψζ)n=[0]Ψζ. If ([s]Ψζ)n=[0]Ψζ, then ζ(sn0)=1 and so ζ((sn))=ζ(sn0)=1. By similar way, we can prove that if ([t]Ψζ)n=[0]Ψζ, then ζ(tn)=1 Therefore, in any case, we have ζ((st))ζ((sn))ζ((tn)) for some nN.. Therefore ζ is a fuzzy primary filter.

Conclusions and discussion

In this study, we have explored the concept of fuzzy ideals and fuzzy filters within a bounded semihoop, delving into their properties and characteristics. Additionally, we have examined various characterizations of fuzzy ideals and filters derived from a given fuzzy subset. Our investigation also encompassed prime fuzzy ideals, fuzzy primary ideals, prime fuzzy filters, fuzzy primary filters, along with their respective characterizations. Furthermore, we have delved into the fuzzy congruence relation in connection to fuzzy (primary) ideals and filters. These findings not only enrich the field of fuzzy set theory but also offer valuable insights into the broader exploration of bounded semihoops and their associated structures. Looking ahead, we plan to delve into the study of soft semihoops and their corresponding structures in future research endeavors.

The study of fuzzy ideals and filters in bounded semihoops offers a unique opportunity to bridge the gap between crisp mathematical structures and fuzzy logic. By delving into the properties, characterizations, and relationships of these fuzzy constructs, we can gain insights into how they interact within the framework of bounded semihoops.

Disclosure statement

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

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