Introduction to neutrosophy and neutrosophic environment
Florentin Smarandache*; Said Broumi†; Prem Kumar Singh‡; Chun-fang Liu§; V. Venkateswara Rao¶; Hai-Long Yang‖; Ion Patrascu#; Azeddine Elhassouny*** Department of Mathematics, University of New Mexico, Gallup, NM, United States † Laboratory of Information Processing, University Hassan II, Casablanca, Morocco ‡ Amity Institute of Information Technology and Engineering, Amity University, Noida, India § College of Science, Northeast Forestry University, Harbin, China ¶ Division of Mathematics, Department of S&H, VFSTR, Guntur, India ‖ College of Mathematics and Information Science, Shaanxi Normal University, Xi’an, China # Mathematics Department, Fratii Buzesti College, Craiova, Romania ** Rabat IT Center, ENSIAS, Mohammed V University in Rabat, Rabat, Morocco
Abstract
This chapter provides an overview on neutrosophy along with its mathematical developments over the last 2 decades. This will educate the readers about neutrosophy as a generalization of dialectics with its several mathematical algebra, precalculus and calculus. In addition, the nonstandard neutrosophic set (NS), the standard NS, the hesitant NS, and their extension to a complex fuzzy environment are also discussed. Moreover, the neutrosophic aggregation operators; the neutrosophic cognitive maps; the neutrosophic overset, underset, and offset; the neutrosophic crisp set; the refined NS; and the law of included multiple middle are also addressed. Furthermore, this chapter reports the neutrosophic algebraic structures, neutrosophic graphs, neutrosophic triplets, neutrosophic duplets, neutrosophic multisets, and the extension of crisp/fuzzy/intuitionistic fuzzy/NSs to plithogenic sets in detail with their mathematical expressions.
LTM, LIM, and LFMlower truth, indeterminate, and false membership
NCSneutrosophic cubic set
NIMFnegative interval membership function
NMFfalsity membership function
NMFnegative membership function
NSneutrosophic set
PIMFpositive interval membership function
PMFpositive membership function
PMFpositive membership function
PSplithogenic set
SVNLSsingle-valued neutrosophic linguistic set
SVNRSsingle-valued neutrosophic rough set
SVNSsingle-valued neutrosophic set
TMFtruth membership function
UTM, UIM, and UFMupper truth, indeterminate, and false membership
1 Introduction
The theory of fuzzy sets was introduced at the earliest by Zadeh (1965) for dealing with the uncertainty that exists in given datasets. In this section, a problem is developed that the FSs represents acceptation, rejection and uncertain parts via a single-valued membership defined in [0, 1]. It is unable to represent the indeterminacy independently. In 1995, the theory of neutrosophical logic and sets was proposed by Smarandache (1995, 1998). Neutrosophy leads to an entire family of novel mathematical theories with an overview of not only classical but also fuzzy counterparts. The reason is that a fuzzy set representing uncertainty exists in the attributes using single-valued membership. In this case, one cannot represent when win, loss, and draw match independently. To represent this, we need to characterize them lay in membership-values of truth, falsity, and indeterminacy. This makes it necessary to extend the fuzzy sets beyond acceptation and rejection regions using single-valued neutrosophic values (Smarandache, 1998; Ye, 2014). It contains truth, falsity, and indeterminacy membership values for any given attribute. The most interesting point is that all these three functions are completely independent, and one function is not affected by another. NS essentially studies the starting point, environment, and range of neutralities and their exchanges with ideational ranges. One of the suitable examples is that the win, draw, or loss condition of any game cannot be written independently using the properties of FS. Similarly, there are many examples that contain uncertainty and indeterminacy such as the opinion of people toward a leader and other areas shown in Ramot, Milo, Friedman, and Kandel (2002), Ye (2014b), and Torra and Namkawa (2009). In many cases, some people support a leader, some people reject a leader, and some people vote NOTA or they abstain. To approximate these types of uncertainties, the mathematics of neutrosophic theory are extended to several environments such as hesitant neutrosophic sets (NSs) (Ye, 2015), bipolar environments (Ali & Smarandache, 2015; Deli, Ali, & Smarandache, 2015; Broumi, Bakali, et al., 2019; Broumi, Nagarajan, et al., 2019; Broumi, Talea, Bakali, Smarandache, & Singh, 2019), complex NSs (Ali, Dat, Son, & Smarandache, 2018), rough sets (Bao & Yang, 2017; Bao, Hai-Long, & Li, 2018; Guo, Liu, & Hai-Long, 2017; Yang, Bao, & Guo, 2018; Yang, Zhang, Guo, Liu, & Liao, 2017; Liu, Hai-Long, Liu, & Yang, 2017), and cubic sets (Aslam, Aroob, & andYaqoob, 2013; Jun, Kim,& Kang, 2010, 2011; Jun, Kim, & Yang, 2012; Jun, Smarandache, & Kim, 2017) with applications in various fields (Broumi et al., 2018; Broumi, Bakali, et al., 2019; Broumi, Talea, et al., 2019; Singh, 2017, 2018a, 2018b, 2018c, 2019; Smarandache, 2017). In this chapter, we will try to provide a comprehensive overview of those mathematical notations.
To measure the future perspective of any given event, this chapter also discusses the properties of cubic sets as a new technique in the NS theory. Jun et al. (2012) introduced cubic sets in both FS and valued interval fuzzy sets. The author also has distinct internal (external) cubic sets and has studied some of their properties. The designs of cubic algebras/ideals in every Boolean Abelian group and commutative algebra with its implication, that is, BCK/BCI algebra, are also introduced in Jun et al. (2010). Jun et al. (2011) proposed the notion of cubic q-ideals in BCI algebras where BCK/BCI are the algebraic structure by applying BCK logic. This abbreviation is provided by B, C, and K and the relation of both a cubic ideal and a cubic q-ideal. In addition, they recognized conditions for a cubic ideal to be cubic q-ideal and the characterizations of a cubic q-ideal and a cubic extension property for a cubic q-ideal. The idea of a cubic sub LA-semihypergroup is considered by Aslam et al. (2013). The same authors defined some results on cubic hyper ideals and cubic bi-hyper ideals in left almost-semihypergroups. The reader can refer to Singh (2018a, 2018b) and Broumi et al. (2018) for more information about other types of NSs not included in this chapter. Some researchers tried to incorporate the algebra of NSs and its extension for knowledge-processing tasks in various fields. Recently, it was extended to n-valued neutrosophic context and its graphical visualization for applications in various fields for multidecision processes.
Other parts of this chapter are organized in the following way: The preliminaries are shown in Section 2. Sections 3–14 contains each distinct extension of a NS with its mathematical algebra for better understanding, followed by conclusions and references.
2 Preliminaries
This section contains preliminaries to understand the NS.
Definition 1
Crisp set
It defines any set ξ based on a given universal set U such that an element belongs to ξ or not. One of the examples is a student who is either present or absent in the class. It does not define the exact membership of whether an element belongs to the set.
Let us suppose E is a universe, then the FS(ξ) can be defined as mapping μX(k) : ξ → [0, 1] for each k ∈ ξ. In this case, each element is represented using the defined membership values μξ within [0, 1]. It represents the degree of an element that belongs to the given set. In this method, it provides representation of any element in the given set via a soft boundary.
The IFS is a generalization of FS. It represents the acceptation or rejection part of any attribute simultaneously. The IFS A can be defined by A = {x, μX(k), νX(k)/k ∈ ξ} where μA(k) : ξ → [0, 1], νA(k) : ξ → [0, 1] for each k ∈ ξ such that 0 ≤ μA(k) + νA(k) ≤ 1. Here, μA(k) : ξ → [0, 1] denotes degrees of membership andνA(k) : ξ → [0, 1] denotes nonmembership of k ∈ A, respectively.
Definition 4
Interval-valued fuzzy set
The interval-valued fuzzy set is nothing but an extension of FS. It provides a way to represent the membership for belonging of any attribute. The interval-valued fuzzy set A over a universe ξ is defined by
A={[A−(k),A+(k)]/k∈ξ},
(1)
where A−(k), A+(k) represent the lower boundary and upper boundary for the given membership degrees within interval [0, 1].
Definition 5
Cubic set
The cubic set provides a way to represent the interval-valued fuzzy set with more predictive analytics. It can be defined with the help of an interval-valued fuzzy set A(x) as well as a single-valued fuzzy set μ(k) as Ξ = {< x, A(k), μ(k) > /k ∈ ξ}. It means one can also represent the cubic set as 〈A, μ〉 for precise representation of any event.
The interval cubic set is nothing but an extension of the cubic set where the single-valued fuzzy set is replaced by interval-valued set, that is, Ξ = 〈A, μ〉 where A(k) is the interval-valued fuzzy set and the μ(k) lies between them as:
A−(x)≤μ(x)≤A+(x),∀k∈ξ.
(2)
Example 2
Let τ = 〈A, λ〉 ∈ CNX where CNX is the set of cubic sets. A(x) = 〈[0.1, 0.3], [0.4, 0.6], [0.7, 0.8]〉 and λ(x) = 〈0.2, 0.5, 0.6〉 for every k in ξ. Then τ = 〈A, λ〉 is an interval cubic set.
Definition 7
External cubic set
The external cubic set Ξ = 〈A, μ〉 is a set in which the FS μ(k) membership values do not belong to the given interval set A(x) meaning
μ(x)∉(A−,(k),A+(k))∀k∈ξ.
(3)
Example 3
Let τ = 〈A, λ〉 ∈ CNX where CNX is the set of cubic sets. A(k) = 〈[0.1, 0.3], [0.4, 0.6], [0.7, 0.8]〉 and λ(k) = 〈0.4, 0.2, 0.3〉 for every k in ξ. Then τ = 〈A, λ〉 is an external cubic set.
Definition 8
Neutrosophic set
The NS consists of reptile functions, namely truth, indeterminacy, and false, (T, I, F), independently. Each of these values lies between 0 and 1 and does not depend on them. The boundary conditions of the sum of these membership degrees are 0 ≤ T + I + F ≤ 3. In this, 0 is hold for the universal false cases and 3 are the universal truth cases three memberships, that is,
λ={〈x:T,I,F〉:x∈ξ}.
(4)
Definition 9
Interval neutrosophic set
The interval-valued neutrosophic set consists of reptile functions, namely truth, indeterminacy, and false, (T, I, F). Each of these values is defined in the following form [T−, T+], [I−, I+], and [F−, F+]. All these values lie between 0 and 1, and we denote this as
This set contains triplets having true, false, and indeterminacy membership values that can be characterized independently, TN, IN, FN, in [0,1]. It can be abbreviated as follows:
Let ξ be a nonempty set and its element is k, the NS N in ξ is termed by
A={〈k;TA(k),IA(k),FA(k)〉|k∈ξ}
(8)
which is characterized by a TMF TN(k), an IMF IN(k), and an FMF FN(k), respectively, where
TN(k):ξ→]0−1+[
IN(k):ξ→]0−1+[
FN(k):ξ→]0−1+[
The functions TN(k), IN(k), FN(k) in ξ are real standard or nonstandard subsets of ]− 0, 1+[. The sum of TN(k), IN(k), FN(k) does not have any restrictions, that is
−0≤supTN(x)+supIN(k)+supFN(k)≤3+.
(9)
Here ]− 0, 1+[ is named the nonstandard subset, which is the extension of real standard subsets [0,1] where the nonstandard number 1+ = 1 + ɛ, “1” is named the standard part, and “ɛ” is named the nonstandard part. − 0 = 0 − ɛ, “0” is the standard part and “ɛ” is named the nonstandard part, where ɛ is closed to positive real number zero.
In this case, the left and right endpoints of the nonstandard fuzzy membership values represent ambiguity and uncertainty while describing the practical problems.
It is well known that the NS (N) in use contains a TMF TN(k), an IMF IN(k), and a FMF FN(k), respectively. Each of them can contain the membership values as given below in case of the standard format:
TN(k):ξ→[0,1]
IN(k):ξ→[0,1]
FN(k):ξ→[0,1]
Then,
N={〈k;TN(k),IN(k),FN(k)〉|k∈ξ}
(10)
is termed an SVNS.
If the nonempty set ξ has only one element x, then we call the NS N the single-valued neutrosophic number (SVNN). We abbreviate it as N = 〈k; TN, IN, FN〉.
Generally, if IN(k) = 0, the SVNS A is reduced to the IFSN = {〈k; TN(k), FN(k)〉| k ∈ ξ}. If IN(k) = FN(k) = 0, then it is reduced to FSN = {〈k; TN(k)〉| k ∈ ξ}. The FS, IFS, and NS relationships are shown in Fig. 1.
Let us suppose that ξ is a series of real number points presented by k, then the NS will be a subset of those points, that is, N ⊂ ξ having TN(k), IN(k), and FN(k). It describes the TM degree, the IM degree, and the FM degree for the given element k ∈ ξ with respect to the NS N. The overset of NS can be defined as follows:
where TN(k), IN(k), FN(k): ξ → [0, Ω], 0 < 1 < Ω and Ω are named overlimit, then there exists at least one element in N such that it has at least one neutrosophic component > 1, and no element has a neutrosophic component < 0.
Let us suppose that ξ is a series of points (objects) with basic elements in ξ presented by k and the NS N ⊂ ξ. Here TN(k), IN(k), FN(k) ts are the TM degree, the IM degree, and the FM degree for the element x ∈ ξ with respect to the NS N. In this case, the underset of neutrosophic values can be defined as:
In this case, TN(k), IN(k), FN(k): ξ → [Ψ, 1], Ψ < 0 < 1 and Ψ are named the lower limit. It shows that there exists at least one element in A that has one neutrosophic component value < 0, and no element has a neutrosophic component value > 1.
Let us suppose that ξ is a series of points (objects) with basic elements in ξ presented by k and the NS N ⊂ ξ. Let TN(k), IN(k), FN(k) represent the TM degree, the IM degree, and the FM degree for the given element k ∈ ξ with respect to the NS N. The offset can be defined as follows:
In this case, TNk, INk, FN(k): ξ → [Ψ, 1], Ψ < 0 < 1 < Ω and Ψ are named the underlimit while Ω is named the overlimit. It means there exists some elements in N such that at least one neutrosophic component > 1 and at least another neutrosophic component < 0.
The complement of an SVN overset/underset/offset N is abbreviated as C(N) and is defined by
C(N)={(k,⟨FN(k),Ψ+Ω−IN(x),TN(k)>),k∈ξ}.
(20)
Definition 20
Union and intersection of overset/underset/offset (Smarandache, 2016)
The intersection of two SVN overset/underset/offset N and M is an SVNN overset/underset/offset (C) represented as follows: C = N ∩ M and is represented by
Ye (2015) has developed the concepts of interval neutrosophic linguistic sets (INLS) and interval neutrosophic linguistic variables by combining a linguistic variable with an interval neutrosophic set (INS).
5 An interval-valued neutrosophic linguistic set
Definition 24
An interval-valued neutrosophic linguistic set (Ye, 2015)
Let ξ be a series of points with basic elements in ξ presented by k, then an interval neutrosophic linguistic set N (IVNLS) in ξ is defined as
with the condition 0 ≤ TN(k) + IN(k) + FN(k) ≤ 3, for any k ∈ ξ. sθ(x) is an uncertain linguistic term. The functions TN(k), IN(k), and FN(k) express, respectively, the TM degree, the IM degree, and the FM degree of the element k in ξ belonging to the linguistic term sθ(x), which is another continuous form of the linguistic set S.sθ, sρ, sμ, sν are four linguistic terms, and s0 ≤ sθ ≤ sρ ≤ sμ ≤ sν ≤ sl − 1 if 0 ≤ θ ≤ ρ ≤ μ ≤ ν ≤ l − 1, then the trapezoid linguistic variable (TLV) is termed as ⌢s=[sθ,sρ,sμ,sν], and ⌢s represents a set of the TLVs.
Definition 25
Linguistics variable
Let ˉS={sθ|s0≤sθ≤sl−1,θ∈[0,l−1]} be the linguistic set in its continuous form S.sθ, sρ, sμ, sν are four linguistic terms, and s0 ≤ sθ ≤ sρ ≤ sμ ≤ sν ≤ sl − 1 if0 ≤ θ ≤ ρ ≤ μ ≤ ν ≤ l − 1, then the TLV is defined as ⌢s=[sθ,sρ,sμ,sν], and ⌢s represents a set of the TLVs.
where sθ(x),sρ(x)∈⌢s, TN(k) ⊆ [0, 1],IN(k) ⊆ [0, 1], FN(k) ⊆ [0, 1] with the condition 0 ≤ TN(k) + IN(k) + FN(k) ≤ 3, for any x ∈ ξ. [sθ(x), sρ(x)] is an uncertain linguistic term. The functions TN(k), IN(k), and FN(k) express, respectively, the TM degree, the IM degree, and the FM degree of the element x in ξ belonging to the linguistic term[sθ(x), sρ(x)].
Definition 27
(Ye, 2015): Operations on linguistics neutrosophic set
For any given two SVNULVNs ˜α1=〈[sθ(˜α1),sρ(˜α1)],(T(˜α1),I(˜α1),F(˜α1))〉, ˜α2=〈[sθ(˜α2),sρ(˜α2)],(T(˜α2),I(˜α2),F(˜α2))〉, λ > 0 is a constant, and their operational rules are defined as follows:
It is well known that linguistics contains bipolar information, that is, positive and negative membership values simultaneously. To deal with these types of datasets, the NS is extended as a bipolar neutrosophic set (BNS).
Suppose ξ is a series of points (objects) with basic elements in ξ presented by x. A bipolar neutrosophic set N (BNS) in ξ is defined as in the following form
where TP, IN+, FP : ξ → [1, 0] and TP, IN−, FP : ξ → [− 1, 0] are the PMFs NMFs. We call TN+(k), IN+(k), FN+(k) the TMF, IMF, and FMF of an element k ∈ s. The NMF degree TN−(k), IN−(k), FN−(k) represents the TMF, IMF, and FMF of an element x ∈ ξ. If the set has only one element, then we call N a BNN and define it by
NBNS=〈T+A,I+A,F+A,T−A,I−A,F−A〉.
(35)
In case the uncertainty in the dataset fluctuates at given intervals of time, then the complex NS is defined.
Suppose that ξ is a set of some points denoted as k. A complex neutrosophic set (CNS) is defined on the set ξ through the definition of three membership functions, TN(k), IN(k), FN(k), and we call them the TMF, the IMF, and the FMF, respectively. Here, we allocate a complex-valued grade of TN(k), IN(k), and FN(k) in N for any k ∈ ξ. All the values TN(k), IN(k), and FN(k) and the sum values of these three functions are all in the complex plane unit circle, and their forms are as follows.
The complex grade of TMF is characterized by a truth amplitude term ρN(k) and a truth phase term μN(k).
In addition, the complex degree of IMF is defined as an indeterminate amplitude term, and the complex grade of IMF is defined as an indeterminate term qN(k) and an indterminate phase term vN(x).
The complex grade of the FMF is defined by the false amplitude term rN(k) and a false phase term ωN(x), respectively. It should be noted that the truth amplitude term ρN(x) is equal to | TN(k)|, the amplitude of TN(k). The indeterminate amplitude term qN(x) is equal to | IN(k)| and the false amplitude term rN(k) is equal to | FN(k)|.
Definition 30
Union and intersection of CNSs
Suppose N and M are two CNSs in ξ, where N = {(k, TN(k), IN(k), FN(k)) : k ∈ ξ} andM = {(k, TM(k), IM(k), FM(k)) : k ∈ ξ}.
Then the union of N and M is termed as N ∪CNSM and we denote it as
N∪CNSM={(k,TN∪M(k),IN∪M(k),FN∪M(k)):k∈ξ},
(40)
where the TMF nTN ∪ M(k), the IMF IN ∪ M(k), and the FMF FN ∪ M(k) are denoted by
where ∨ and ∧ represent the operators max and min, respectively.
The phase term of the complex truth function, the complex indeterminacy function, and the complex falsehood function belongs to (0, 2π) and the definitions of the phase term are as follows:
Suppose ξ is a set of some points with basic elements in ξ presented by x. A bipolar complex neutrosophic set A (BCNS) in ξ is defined in the following form
where TP, I1+, FP : X → [1, 0] and TP, I1−, FP : X → [− 1, 0]. The positive membership degree T1+(k), I1+(k), F1+(k) represents the TM, the IM, and the MF of an element x ∈ ξ corresponding to the given property, whereas the negative membership degree T1−(k), I1−(k), F1−(k) represents the TM, the IM, and the FM of an element k ∈ ξ to some implicit counterproperty. A BCNN can be abbreviated as follows:
Suppose there are two BCNSs BCN1 =(T1+ eiT2+,I1+ eiI2+,F1+ eiF2+,T1− eiT2−,I1− eiI2−,F1− eiF2−) and BCN2 =(T3+ eiT4+,I3+ eiI4+,F3+ eiF4+,T3− eiT4−,I3− eiI4−, F3− eiF4−). BCN1 is contained in the other BCN2 detailed as BCN1 ⊆ BCN2 if
Suppose ξ is a series of points (objects) basic elements in ξ presented by k. An ICNS is defined on ξ, which is characterized through a function ITMF ˜TN(k)=[TLN(k),TUN(k)], an interval IMF ˜IN(k), and an interval FMF ˜FN(k) that assigns a complex-valued membership grade to ˜TN(k),˜IN(k),˜FN(k) for any k ∈ ξ. The values of ˜TN(k),˜IN(k),˜FN(k) and their sum take some values within a complex plane unit circle. The forms of the functions are below:
˜TN(k)=[pLN(k),pUN(k)]⋅ei[μLN(k),μUN(k)],
˜IN(k)=[qLN(k),qUN(k)]⋅ei[vLN(k),vUN(k)],and
˜FN(k)=[rLN(x),rUN(k)]⋅ei[ωLN(k),ωUN(k)].
(52)
All the amplitude and phase terms are real valued. And pNL(k), pNU(k), qNL(k), qNU(k), rNL(k) and rNU(k) ∈ [0, 1], whereas μN(k), νN(k), ωN(k) ∈ (0, 2π], such that the condition
0≤pUN(k)+qUN(k)+rUN(k)≤3
(53)
is satisfied. TA(x) an ICNS ˜A can thus be termed in the defined form as:
˜N={〈k,TN(k)=aT,IN(k)=aI,FN(k)=aF〉:k∈ξ},
(54)
where TN : ξ. → {aT : aT ∈ C, | aT | ≤ 1}, IN : ξ. → {aI : aI ∈ C, | aI | ≤ 1}, FN : ξ. → {aF : aF ∈ C, | aF | ≤ 1}, and also | TNU(k) + INU(k) + FNU(k)| ≤ 3.
Let ξ be a series of points with basic elements in ξ presented by k. An interval-valued bipolar neutrosophic set N (IVBNS) in ξ is abbreviated in the following form
˜AIVBNS={〈k,tp,ip,fp,tn,in,fn〉:k∈ξ},
(65)
where tp = [TLp, TMp], ip = [ILp, IMp], fp = [FLp, FMp], tn = [TLn, TMn], in = [ILn, IMn], fn = [FLn, FMn], and TLpTP, TMpILpTP, IMp,FLpTP, FMpFP: ξ →[0, 1] and TLnTP, TMnILnTP, IMn, FLnTP, FMn: ξ →[− 1, 0]. The PIM degree where TLpTP, TMpILpTP, IMp,FLpTP, FMpFP denotes the LTM, UTM, LIM, UIM, and LFM, UFM of an element k ∈ ξ corresponding to a BNS A and the NIM degree TLnTP, TMnILnTP, IMn,FLnTP, FMn: denotes LTM, UTM, LIM, UIM, and LFM, UFM of an element k ∈ ξ to some implicit counterproperty corresponding to an IVBNS A.