The calculation of the so-called weighted expected value is one of possible methods to deffuzify a fuzzy number.
For \(w=0.5\) we get the ordinary expectedValue
.
# S4 method for FuzzyNumber
weightedExpectedValue(object, w=0.5, ...)
a fuzzy number
additional arguments passed to expectedInterval
a single numeric value in [0,1]
Returns a single numeric value.
The weighted expected value of \(A\) is defined as
\(EV_w(A) := (1-w) EI_L(A) + w EI_U(A)\),
where \(EI\) is the expectedInterval.
Other FuzzyNumber-method:
Arithmetic
,
Extract
,
FuzzyNumber-class
,
FuzzyNumber
,
alphaInterval()
,
alphacut()
,
ambiguity()
,
as.FuzzyNumber()
,
as.PiecewiseLinearFuzzyNumber()
,
as.PowerFuzzyNumber()
,
as.TrapezoidalFuzzyNumber()
,
as.character()
,
core()
,
distance()
,
evaluate()
,
expectedInterval()
,
expectedValue()
,
integrateAlpha()
,
piecewiseLinearApproximation()
,
plot()
,
show()
,
supp()
,
trapezoidalApproximation()
,
value()
,
width()
Other deffuzification:
expectedValue()
,
value()
Other characteristics:
ambiguity()
,
expectedValue()
,
value()
,
width()