simWWLWW9 {ipsfs}

SFS similarity measure simWWLWW9

Description

SFS similarity measure values using simWWLWW9 computation technique with membership,non-membership, indeterminacy membership, and refusal membership values of two objects or set of objects.

Usage

simWWLWW9(ma, na, mb, nb, ia, ib, ra, rb, 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

ra

SFS refusal membership values for the data set x

rb

SFS refusal 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

G. Wei, J. Wang, M. Lu, J. Wu, and C. Wei. Similarity measures of spherical fuzzy sets based on cosine function and their applications. IEEE Access, 7:159069 - 159080, 2019.

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)
ra<-rmemSFS(ma,na,ia)
mb<-memG(a1,b1,y)
nb<-nonmemS(mb,lam)
ib<-imemSFS(mb,nb)
rb<-rmemSFS(mb,nb,ib)
k<-1
simWWLWW9(ma,na,mb,nb,ia,ib,ra,rb,k)
#[1] 0.04488958 0.04334510 0.08280306 0.08280306