Fuzzy.BellMFType
Generalised Bell membership function type

BellMF(a, b, c)

Properties
----------
a, b and c the usual bell parameters with c being the center
Fuzzy.GaussianMFType

Gaussian membership function type

GaussianMF(center, sigma)

Properties
----------
center is the center of the distribution
sigma determines width of the distribution
Fuzzy.SigmoidMFType
Sigmoid membership function type

SigmoidMF(a, c, limit)

Properties
----------
a controls slope
c is the crossover point
limit sets the extreme limit
Fuzzy.TrapezoidalMFType
Trapezoidal membership function type

TrapezoidalMF(l_bottom_vertex, l_top_vertex, r_top_vertex, r_bottom_vertex)

Properties
----------
l_bottom_vertex, l_top_vertex, r_top_vertex and r_bottom_vertex are the vertices of the trapezoid, in order
Fuzzy.TriangularMFType
 Triangular membership function type

TriangularMF(l_vertex, center, r_vertex)

Properties
----------
l_vertex, center and r_vertex are the vertices of the triangle, in order
Fuzzy.algebraic_productMethod
Compute the algebraic product of the tmp_strengths vector

algebraic_product(tmp_strengths<:AbstractFloat)
Fuzzy.algebraic_sumMethod
Compute the algebraic sum of the tmp_strengths vector

algebraic_sum(tmp_strengths<:AbstractFloat)
Fuzzy.bounded_differenceMethod
Compute the bounded difference of the tmp_strengths vector

bounded_difference(tmp_strengths<:AbstractFloat)
Fuzzy.bounded_sumMethod
Compute the bounded sum of the tmp_strengths vector

bounded_sum(tmp_strengths<:AbstractFloat)
Fuzzy.chart_prepareMethod
Create points

eval_fis(sets_dict, input_point_vector)

Parameters
----------
sets_dict dictionary of membership functions
input_point_vector array of points
Fuzzy.defuzzMethod
Defuzzifies the output using the given firing strengths

defuzz(firing_strengths, rules, output_mfs_dict, defuzz_method)

Parameters
----------
firing_strengths is a Vector of firing strengths
one for each output membership function
rules is a Vector of Rule
output_mfs_dict is a Dict of output membership functions
defuzz_method is the method for defuzzification
"MOM" - Mean of Maximum
"WTAV" - Weighted Average
Fuzzy.drastic_productMethod
Compute the drastic product of the tmp_strengths vector

drastic_product(tmp_strengths<:AbstractFloat)
Fuzzy.drastic_sumMethod
Compute the drastic sum of the tmp_strengths vector

drastic_sum(tmp_strengths<:AbstractFloat)
Fuzzy.einstein_productMethod
Compute the Einstein product of the tmp_strengths vector

einstein_product(tmp_strengths<:AbstractFloat)
Fuzzy.einstein_sumMethod
Compute the Einstein sum of the tmp_strengths vector

einstein_sum(tmp_strengths<:AbstractFloat)
Fuzzy.eval_fisFunction
Evaluates the FIS

eval_fis(fis, input_values,defuzz_method = "WTAV")

Parameters
----------
fis is the inference system to evaluate
input_values is a Vector of inputs
defuzz_method is the method for defuzzification, see defuzz function definition
Fuzzy.eval_fisMethod
Evaluates the FIS

eval_fis(fis, input_values)

Parameters
----------
fis is the inference system to evaluate
input_values is a Vector of inputs
Fuzzy.hamacher_productMethod
Compute the Hamacher product of the tmp_strengths vector

hamacher_product(tmp_strengths<:AbstractFloat)
Fuzzy.hamacher_sumMethod
Compute the Hamacher sum of the tmp_strengths vector

hamacher_sum(tmp_strengths<:AbstractFloat)
Fuzzy.maximum_valueMethod
Compute the maximum value of the tmp_strengths vector

maximum_value(tmp_strengths<:AbstractFloat)
Fuzzy.minimum_valueMethod
Compute the minimum value of the tmp_strengths vector

minimum_value(tmp_strengths<:AbstractFloat)