evalmf {FuzzyR}

Evaluate fuzzy membership function

Description

To obtain the corresponding membership grade(s) for given crsip input(s) x

Usage

evalmf(...)

Arguments

...

For singleton fuzzification: x, mf.type, mf.params; x, mf.
Four additional parameters need to be used for non-singleton fuzzification: fuzzification.method, fuzzification.params, firing.method and input.range. See details below for more information.

Details

• x - the crisp input(s) on the universe of discourse for corresponding antecedent membership function
  

• mf.type - The type of fuzzy membership function
  

• mf.params - The parameters for the given type of membership function
  

• mf - the membership function generated by genmf

• fuzzification.method, fuzzification.params, firing.method and input.range - see addvar

Usage:

1. evalmf(x, mf.type, mf.params)

2. evalmf(x, mf)

3. evalmf(x, mf.type, mf.params, fuzzification.method, fuzzification.params, firing.method, input.range)

4. evalmf(x, mf, fuzzification.method, fuzzification.params, firing.method, input.range )

Value

Membership grade(s)

Author(s)

Chao Chen

Examples

evalmf(5, mf.type=gbellmf, mf.params=c(1,2,3))
evalmf(1:10, mf.type=gbellmf, mf.params=c(1,2,3))
evalmf(1:10, mf.type=gbellmf, mf.params=c(1,2,3), fuzzification.method='gauss',
         fuzzification.params=1, firing.method='tnorm.min.max', input.range=c(0,10))

mf <- genmf('gbellmf', c(1,2,3))
evalmf(5, mf)
evalmf(1:10, mf)
evalmf(1:10, mf, fuzzification.method='gauss', fuzzification.params=1,
         firing.method='tnorm.min.max', input.range=c(0,10))