simSGFDK5 {ipsfs} | R Documentation |
SFS similarity measure simSGFDK5
Description
SFS similarity measure values using simSGFDK5 computation technique with membership,non-membership, and indeterminacy membership values of two objects or set of objects.
Usage
simSGFDK5(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
S. A. S. Shishavan, F. K. Gundogdu, E. Farrokhizadeh, Y. Donyatalab, and C. Kahraman. Novel similarity measures in spherical fuzzy environment and their applications. Engineering ApplicationsĀ of Artificial Intelligence, 94:103837, 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
simSGFDK5(ma,na,mb,nb,ia,ib,k)
#[1] 0.6563487 0.6447030 0.8547821 0.8547821