L: Introducing the form of L fuzzy number

Description Usage Arguments Value Author(s) References Examples

View source: R/L.R

Description

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, α, β)L . Function L introduce a total form for L fuzzy number to computer.

Usage

1
L(m, m_l, m_r)

Arguments

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

Value

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.

Author(s)

Abbas Parchami

References

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).

Examples

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# 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)
  }

Example output

Attaching package: 'Calculator.LR.FNs'

The following object is masked from 'package:base':

    sign

function (m, m_l, m_r) 
{
    c(m, m_l, m_r, 0.5)
}

Calculator.LR.FNs documentation built on May 2, 2018, 5:06 p.m.