simKKDKS {ipsfs}

SFS similarity measure simKKDKS

Description

SFS similarity measure values using simKKDKS computation technique with membership,non-membership, and indeterminacy membership values of two objects or set of objects.

Usage

simKKDKS(ma, na, mb, nb, ia, ib, k)

Arguments

ma

SFS membership values for the data set x computed using either triangular or trapezoidal or guassian membership function

na

SFS non-membership values for the data set x computed using either Sugeno and Terano's or Yager's non-membership function

mb

SFS membership values for the data set y computed using either triangular or trapezoidal or guassian membership function

nb

SFS non-membership values for the data set y computed using either Sugeno and Terano's or Yager's non-membership function

ia

SFS indeterminacy membership values for the data set x

ib

SFS indeterminacy membership values for the data set y

k

A constant value, considered as 1

Value

The SFS similarity values of data set y with data set x

References

M. J. Khan, P. Kumam, W. Deebani,W. Kumam, and Z. Shah. Distance and similarity measures for spherical fuzzy sets and their applications in selecting mega projects. Mathematics, 8(4):519, 2020.

Examples

x<-matrix(c(12,9,14,11,21,16,15,24,20,17,14,11),nrow=4)
y<-matrix(c(11,21,6),nrow=1)
a<-mn(x)
b<-std(x)
a1<-mn(y)
b1<-std(y)
lam<-0.5
ma<-memG(a,b,x)
na<-nonmemS(ma,lam)
ia<-imemSFS(ma,na)
mb<-memG(a1,b1,y)
nb<-nonmemS(mb,lam)
ib<-imemSFS(mb,nb)
k<-1
simKKDKS(ma,na,mb,nb,ia,ib,k)
#[1] 0.5726216 0.3223250 0.2791418 0.2791418