TFuzzyVariable Class

TGCollectionItem
FuzzyLogic.TFuzzyVariable

Delphi

type
TFuzzyVariable = class(TGCollectionItem)
end;

	Name	Description
	Create(TCollection)	Overloaded. Initializes a new instance of the TFuzzyVariable class.
	Create(TCollection,TFuzzySetClass)	Overloaded. Initializes a new instance of the TFuzzyVariable class.
	Destroy	Represents the destructor of the TFuzzyVariable class.

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	Name	Description
	AsString	Returns a string representation of the fuzzy variable. The string representation is parsable by the parser defined in the Parser property
	Collection	Returns the collection of fuzzy variables that this fuzzy variable belongs to
	Comment	Contains a comment about the fuzzy variable. Use this property for any descriptive text you want to define about the fuzzy variable
	Fuzzy	Returns the Fuzzy Logic component that owns this fuzzy variable
	ItemIndex	Returns the current selected fuzzy set in the Items collection, or -1 if none is selected.
	Items	Tracks all the fuzzy sets in the fuzzy variable.
	Maximum	Defines the maximum X value for the fuzzy variable, its universe of discourse.
	Minimum	Defines the minimum X value for the fuzzy variable, its universe of discourse.
	Name	Defines the name of the fuzzy variable.
	SetClass	Represents property SetClass.
	Threshold	Defines the "noise" level of fuzzy sets in the variable. When two fuzzy sets are compared to see if they are equal, all the XY value pairs of the two fuzzy sets are compared. If the minimum Y value of the two fuzzy sets at some X point exceed the threshold, then they equal
	Units	Defines the units of the universe of discourse (the X range units). For example, if the fuzzy variable was temperature, the Units may be 'Celcius' or 'Kelvin'.

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	Name	Description
	AssertRule(TFuzzySet,TFuzzySet,TFuzzySet,TFuzzySet)	Overloaded. Performs implication using correlation rules.
	AssertRule(TFuzzySet[],TFuzzySet[],TFuzzySet,TFuzzySet)	Overloaded. Performs implication using correlation rules.
	AssertRule(TFzyFloat,TFuzzySet,TFuzzySet)	Overloaded. Performs implication using correlation rules.
	Assign(TPersistent)	Copies the Source fuzzy variable into the current fuzzy variable
	AssignTo(TPersistent)	Represents method AssignTo(TPersistent).
	CreateItems	Represents method CreateItems.
	GetCorrelationStrength(TFuzzySet[],TFuzzySet[])	Returns the minimum of the correlation strengths of the Premises matched with the Matchings fuzzy sets
	GetDisplayName	Represents method GetDisplayName.
	Notify(TFuzzySet,TCollectionNotification)	Represents method Notify(TFuzzySet,TCollectionNotification).
	ToString	Returns a string representation of the fuzzy variable. The string representation is parsable by the parser defined in the Parser property
	Update(TFuzzySet)	Represents method Update(TFuzzySet).

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Fuzzy Variables are much like set variables in Pascal. However, unlike Pascal variables, the enumerated items, or terms, in the set are fuzzy and not crisp. Pascal allows enumerated values to either be in or not in the set. Fuzzy variables allow values to be partially in the set. For example, we may define a fuzzy variable which is based on Temperature. Any variable of this type may take fuzzy set (TFuzzySet) values of cold, warm, and hot (or some combination). Cold, warm, and hot are the fuzzy sets which define the terms of the type. Each fuzzy set defines a membership function over the domain of temperature. If, for our example, temperature has a range between 0 and 100 Celsius, Cold could be a fuzzy set that defined any value under 10 Celcius as completely cold (one or True), any value over 50 as not at all cold (zero), and any value in between having a membership between zero and one.

The most important function of the Fuzzy Variable is that it acts as the domain for its fuzzy sets. It defines the universe of discourse (the X range) over which values and sets in the variable may take. Before working with fuzzy sets, you must define a fuzzy variable. Fuzzy sets must have unique names.

Reference

•FuzzyLogic

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