fl::WeightedAverage Class Reference

The WeightedAverage class is a WeightedDefuzzifier that computes the weighted average of a fuzzy set represented in an Aggregated Term. More...

#include <WeightedAverage.h>

Inheritance diagram for fl::WeightedAverage:

Collaboration diagram for fl::WeightedAverage:

Public Member Functions
	WeightedAverage (Type type=Automatic)
	WeightedAverage (const std::string &type)
virtual	~WeightedAverage () FL_IOVERRIDE
virtual std::string	className () const FL_IOVERRIDE
	Returns the name of the class of the defuzzifier. More...
virtual Complexity	complexity (const Term *term) const FL_IOVERRIDE
	Computes the complexity of defuzzifying the given term. More...
virtual scalar	defuzzify (const Term *term, scalar minimum, scalar maximum) const FL_IOVERRIDE
	Computes the weighted average of the given fuzzy set represented in an Aggregated term as \(y = \dfrac{\sum_i w_iz_i}{\sum_i w_i} \), where \(w_i\) is the activation degree of term \(i\), and \(z_i = \mu_i(w_i) \). More...
virtual WeightedAverage *	clone () const FL_IOVERRIDE
	Creates a clone of the defuzzifier. More...
Public Member Functions inherited from fl::WeightedDefuzzifier
	WeightedDefuzzifier (Type type=Automatic)
	WeightedDefuzzifier (const std::string &type)
virtual	~WeightedDefuzzifier () FL_IOVERRIDE
void	setType (Type type)
	Sets the type of the weighted defuzzifier. More...
Type	getType () const
	Gets the type of the weighted defuzzifier. More...
virtual std::string	getTypeName () const
	Returns a string representation of the type of the defuzzifier. More...
virtual Type	inferType (const Term *term) const
	Infers the type of the defuzzifier based on the given term. More...
Public Member Functions inherited from fl::Defuzzifier
	Defuzzifier ()
virtual	~Defuzzifier ()

Static Public Member Functions
static Defuzzifier *	constructor ()
Static Public Member Functions inherited from fl::WeightedDefuzzifier
static std::string	typeName (Type type)
	Returns a string representation of the given type. More...

Additional Inherited Members
Public Types inherited from fl::WeightedDefuzzifier
enum	Type { Automatic, TakagiSugeno, Tsukamoto }
	The Type enum indicates the type of the WeightedDefuzzifier based the terms included in the fuzzy set. More...

Detailed Description

The WeightedAverage class is a WeightedDefuzzifier that computes the weighted average of a fuzzy set represented in an Aggregated Term.

Author

Juan Rada-Vilela, Ph.D.

See also

WeightedAverageCustom

WeightedSum

WeightedSumCustom

WeightedDefuzzifier

Defuzzifier

Since

4.0

Definition at line 37 of file WeightedAverage.h.

Constructor & Destructor Documentation

WeightedAverage() [1/2]

fl::WeightedAverage::WeightedAverage ( Type  type = Automatic )

explicit

WeightedAverage() [2/2]

fl::WeightedAverage::WeightedAverage ( const std::string &  type )

explicit

~WeightedAverage()

virtual fl::WeightedAverage::~WeightedAverage ( )

virtual

Member Function Documentation

className()

virtual std::string fl::WeightedAverage::className ( ) const

virtual

Returns the name of the class of the defuzzifier.

Returns

the name of the class of the defuzzifier

Implements fl::Defuzzifier.

clone()

virtual WeightedAverage* fl::WeightedAverage::clone ( ) const

virtual

Creates a clone of the defuzzifier.

Returns

a clone of the defuzzifier

Implements fl::Defuzzifier.

complexity()

virtual Complexity fl::WeightedAverage::complexity ( const Term *  term ) const

virtual

Computes the complexity of defuzzifying the given term.

Parameters

term	is the term to defuzzify

Returns

the complexity of defuzzifying the given term

Implements fl::Defuzzifier.

constructor()

static Defuzzifier* fl::WeightedAverage::constructor ( )

static

defuzzify()

virtual scalar fl::WeightedAverage::defuzzify ( const Term *  term, scalar  minimum, scalar  maximum  ) const

virtual

Computes the weighted average of the given fuzzy set represented in an Aggregated term as \(y = \dfrac{\sum_i w_iz_i}{\sum_i w_i} \), where \(w_i\) is the activation degree of term \(i\), and \(z_i = \mu_i(w_i) \).

From version 6.0, the implication and aggregation operators are not utilized for defuzzification.

Parameters

term	is the fuzzy set represented as an Aggregated Term
minimum	is the minimum value of the range (only used for Tsukamoto)
maximum	is the maximum value of the range (only used for Tsukamoto)

Returns

the weighted average of the given fuzzy set

Implements fl::Defuzzifier.

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The documentation for this class was generated from the following file:

• fuzzylite/fl/defuzzifier/WeightedAverage.h