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TBaseFuzzyHedge
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Defines the basic hedges available for modifying fuzzy sets, or shapes. Basic Hedges are the basic operations you can perform to modify the shape of fuzzy sets. The regular fuzzy hedges; not, very, somewhat, etc; are variations of these basic hedges.
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TDefuzzificationMethod
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Defines the defuzzification methods for determining a value that best represents a fuzzy set. There are two methods available: center of gravity and mean of maxima.
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TFuzzyCorrelationMethod
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Defines the two fuzzy correlation methods available: Minimum and Product. Fuzzy correlation controls how the truth level (where 0 is completely FALSE and 1 is completely TRUE) of a rule's premise (IF portion) modifies the truth of the rule's consequents, whether fuzzy sets are truncated at the truth level (creating a plateau) or multiplied by the truth level (preserving the shape of the fuzzy set but shrinking it).
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TFuzzyHedge
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Defines the hedges available for modifying fuzzy sets, or shapes.
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TFuzzyInferenceMethod
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Defines the fuzzy inference methods available. Fuzzy Inference controls how assertions are combined with facts already on the fact list. Unlike normal inference where new facts may be asserted, fuzzy inference combines the fact already on the fact list with the new fact.
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TFuzzyOperation
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Defines the method used for finding the intersection (AND) or union (OR) of two fuzzy sets, e.g., hot AND cold or hot OR cold. The default fuzzy operation, Zadeh, is named after fuzzy logic's creator, Lofti Zadeh.
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TFuzzySetType
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Defines the type/shape of the fuzzy set. The default, fstUserDefined, means that the fuzzy set is arbitrarily shaped.
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TFuzzyStreamTokenType
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Defines the possible token data types for a fuzzy logic stream that is being tokenized.
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TXYUpdateType
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Defines what values (X or Y) in a fuzzy set have been updated.
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