# alphacut-methods: Compute Alpha-Cuts In FuzzyNumbers: Tools to Deal with Fuzzy Numbers

## Description

If A is a fuzzy number, then its α-cuts are always in form of intervals. Moreover, the α-cuts form a nonincreasing chain w.r.t. alpha.

## Usage

 ```1 2``` ```## S4 method for signature 'FuzzyNumber,numeric' alphacut(object, alpha) ```

## Arguments

 `object` a fuzzy number `alpha` numeric vector with elements in [0,1]

## Value

Returns a matrix with two columns (left and right alha cut bounds). if some elements in `alpha` are not in [0,1], then `NA` is set.

## See Also

Other FuzzyNumber-method: `Arithmetic`, `Extract`, `FuzzyNumber-class`, `FuzzyNumber`, `alphaInterval()`, `ambiguity()`, `as.FuzzyNumber()`, `as.PiecewiseLinearFuzzyNumber()`, `as.PowerFuzzyNumber()`, `as.TrapezoidalFuzzyNumber()`, `as.character()`, `core()`, `distance()`, `evaluate()`, `expectedInterval()`, `expectedValue()`, `integrateAlpha()`, `piecewiseLinearApproximation()`, `plot()`, `show()`, `supp()`, `trapezoidalApproximation()`, `value()`, `weightedExpectedValue()`, `width()`

Other alpha_cuts: `core()`, `supp()`

## Examples

 ```1 2``` ```A <- TrapezoidalFuzzyNumber(1, 2, 3, 4) alphacut(A, c(-1, 0.4, 0.2)) ```

### Example output

```       L   U
-1.0  NA  NA
0.4 1.4 3.6
0.2 1.2 3.8
```

FuzzyNumbers documentation built on Nov. 15, 2021, 5:09 p.m.