GaussianBellFuzzyNumber {FuzzySTs}

Creates a Gaussian two-sided bell fuzzy number

Description

Creates a Gaussian two-sided bell fuzzy number

Usage

GaussianBellFuzzyNumber(
  left.mean,
  left.sigma,
  right.mean,
  right.sigma,
  alphacuts = FALSE,
  margin = c(5, 5),
  step = 0.01,
  breakpoints = 100,
  precision = 4,
  plot = FALSE
)

Arguments

left.mean

a numerical value of the parameter mu of the left Gaussian curve.

left.sigma

a numerical value of the parameter sigma of the left Gaussian curve.

right.mean

a numerical value of the parameter mu of the right Gaussian curve.

right.sigma

a numerical value of the parameter sigma of the right Gaussian curve.

alphacuts

fixed by default to "FALSE". No alpha-cuts are printed in this case.

margin

an optional numerical couple of values representing the range of calculations of the Gaussian curve written as [mean - 3*sigma; mean + 3*sigma] by default.

step

a numerical value fixing the step between two knots dividing the interval [mean - 3*sigma; mean + 3*sigma].

breakpoints

a positive arbitrary integer representing the number of breaks chosen to build the numerical alpha-cuts. It is fixed to 100 by default.

precision

an integer specifying the number of decimals for which the calculations are made. These latter are set by default to be at the order of 1/10^4 .

plot

fixed by default to "FALSE". plot="TRUE" if a plot of the fuzzy number is required.

Value

If the parameter alphacuts="TRUE", the function returns a matrix composed by 2 vectors representing the left and right alpha-cuts. For this output, is.alphacuts = TRUE. If the parameter alphacuts="FALSE", the function returns a list composed by the Class, the mean, the sigma, the vectors of the left and right alpha-cuts.

Examples

GBFN <- GaussianBellFuzzyNumber(left.mean = -1, left.sigma = 1, 
right.mean = 2, right.sigma = 1, alphacuts = TRUE, plot=TRUE)
is.alphacuts(GBFN)