Table of Contents


Specifying rule processing options

There are four optional statements that, if used, must appear immediately after the RuleSet statement. The statements may appear in any order, and if any statement is entered more than once, the last one takes precedence. These statements give you some control over the processing of the fuzzy inference engine while it is evaluating your rules.

On this page...


AlphaCut

Specifies the threshold at which truth values become insignificant. If the truth value of any antecedent clause falls below the alphacut when the clause is evaluated, the inference engine stops evaluating the rule in which the clause appears.

If left unspecified, the default AlphaCut value is 0.1.

Syntax

   AlphaCut ( <numericValue> )
      

Parameters

       <numericValue>
Is a number from 0.0 to 0.99. If set at 0.0, any clause that evaluates to anything greater than zero is essentially considered true to some degree. If set at 0.99, all clauses must evaluate to 1.0 (boolean true) to be considered true at all. Values between 0.05 and 0.2 may be considered typical, but of course it all depends on your fuzzy variables and their fuzzy set definitions.

Example

   AlphaCut ( 0.20 )
      
Return to top

CorrelationMethod

Specifies the manner in which a rule's consequent fuzzy region is correlated with the rule's antecedent fuzzy truth value.

If left unspecified, the default CorrelationMethod is Product.

Syntax

   CorrelationMethod ( Product | Minimum )
      

Parameters

       Product
Specifies that the membership value of the consequent fuzzy region is the product of the fuzzy region and the truth of the premise. The effect is that the consequent fuzzy region is scaled, preserving its shape. This method is generally used with InferenceMethod(ProductOr) or InferenceMethod(FuzzyAdd).
       Minimum
Specifies that the membership value of the consequent fuzzy region is the minimum of the fuzzy region and the truth of the premise. The effect is that the consequent fuzzy region is truncated at the truth of the premise, creating a plateau. This method is generally used with InferenceMethod(MinMax).

Example

   CorrelationMethod ( Minimum )
      
Return to top

DefuzzifyMethod

Specifies the manner in which a fuzzy set is turned into a crisp numeric value.

If left unspecified, the default DefuzzifyMethod is Centroid.

Syntax

   DefuzzifyMethod ( Centroid | MaxHeight )
      

Parameters

       Centroid
Specifies that a fuzzy set's crisp value is calculated as the weighted mean (center of gravity) of the fuzzy region. Also known as composite moments.
       MaxHeight
Specifies that a fuzzy set's crisp value is calculated from the point that has the highest truth value. Also known as composite maximum.

Example

   DefuzzifyMethod ( Centroid )
      
Return to top

InferenceMethod

Specifies the manner in which a solution variable's fuzzy representation is updated.

If left unspecified, the default InferenceMethod is FuzzyAdd.

Syntax

   InferenceMethod ( FuzzyAdd | MinMax | ProductOr )
      

Parameters

       FuzzyAdd
Specifies that the fuzzy solution set is updated by adding the minimum truth value of the consequent fuzzy region, bounded by 1.0. This method is generally used with CorrelationMethod(Product).
       MinMax
Specifies that the fuzzy solution set is updated by using the maximum of the minumum truth value of the consequent fuzzy set. This method is generally used with CorrelationMethod(Minimise).
       ProductOr
Specifies that the fuzzy solution set is updated by using 1 minus the product of (1 minus the truth value of the consequent fuzzy set) and (1 minus the predicate truth). This method is generally used with CorrelationMethod(Product).

Example

   InferenceMethod ( FuzzyAdd )
      
Return to top
Rule language table of contents.
Fuzzy editor table of contents.
Fuzzy System table of contents.

Last modified: Fri Feb 18 10:58:01 CST 2000