L {Calculator.LR.FNs} | R Documentation |
Considering the definition of LR fuzzy number in LR
, if the left and the right shape functions of a LR fuzzy number are be equal (i.e., L(.) = R(.)
), then LR fuzzy number is a L fuzzy number which denoted by (n, \alpha, \beta)L
.
Function L
introduce a total form for L fuzzy number to computer.
L(m, m_l, m_r)
m |
The core of L fuzzy number |
m_l |
The left spread of L fuzzy number |
m_r |
The right spread of L fuzzy number |
This function help to users to define any L fuzzy number after introducing the left shape function L. This function consider L fuzzy number L(m, m_l, m_r) as a vector with 4 elements. The first three elements are m, m_l and m_r respectively; and the fourth element is considerd equal to 0.5 for distinguish L fuzzy number from LR and RL fuzzy numbers.
Abbas Parchami
Dubois, D., Prade, H., Fuzzy Sets and Systems: Theory and Applications. Academic Press (1980).
Taheri, S.M, Mashinchi, M., Introduction to Fuzzy Probability and Statistics. Shahid Bahonar University of Kerman Publications, In Persian (2009).
# First introduce the left shape function of L fuzzy number
Left.fun = function(x) { (1-x^2)*(x>=0)}
A = L(20, 12, 10)
LRFN.plot(A, xlim=c(0,60), col=2, lwd=2)
## The function is currently defined as
function (m, m_l, m_r)
{
c(m, m_l, m_r, 0.5)
}