RL {Calculator.LR.FNs} | R Documentation |

## Introducing the form of RL fuzzy number

### Description

Considering the definition of LR fuzzy number in `LR`

, it is obvious that ` (n, \alpha, \beta)RL `

will be a RL fuzzy number.
Function `RL`

introduce a total form for RL fuzzy number to computer.

### Usage

```
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

```
# 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*version 1.3 Index]