RL: Introducing the form of RL fuzzy number

Description Usage Arguments Value Author(s) References Examples

View source: R/RL.R

Description

Considering the definition of LR fuzzy number in LR, it is obvious that (n, α, β)RL will be a RL fuzzy number. Function RL introduce a total form for RL fuzzy number to computer.

Usage

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RL(m, m_l, m_r)

Arguments

m

The core of RL fuzzy number

m_l

The left spread of RL fuzzy number

m_r

The right spread of RL fuzzy number

Value

This function help to users to define any RL fuzzy number after introducing the left shape and the right shape functions L and R. This function consider RL fuzzy number RL(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 1 for distinguish RL fuzzy number from LR and L 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 left and right shape functions of RL fuzzy number
Left.fun  = function(x)  { (1-x^2)*(x>=0)}
Right.fun = function(x)  { (exp(-x))*(x>=0)}
A = RL(40, 12, 10)
LRFN.plot(A, xlim=c(0,60), col=1)

## The function is currently defined as
function (m, m_l, m_r) 
{
    c(m, m_l, m_r, 1)
  }

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