AI-FuzzyInference
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FuzzyInference.pm view on Meta::CPAN
Here, all implicated fuzzy sets of the fired rules are combined using
fuzzy operators to generate a single fuzzy set for each of the
output variables.
=head2 Defuzzification
Finally, a defuzzification operator is applied to the aggregated fuzzy
set to generate a single crisp value for each of the output variables.
For a more detailed explanation of fuzzy inference, you can check out
the tutorial by Jerry Mendel at
S<http://sipi.usc.edu/~mendel/publications/FLS_Engr_Tutorial_Errata.pdf>.
Note: The terminology used in this module might differ from that used
in the above tutorial.
=head1 PUBLIC METHODS
The module has the following public methods:
=over 4
Here, all implicated fuzzy sets of the fired rules are combined using
fuzzy operators to generate a single fuzzy set for each of the output
variables.
Defuzzification
Finally, a defuzzification operator is applied to the aggregated fuzzy
set to generate a single crisp value for each of the output variables.
For a more detailed explanation of fuzzy inference, you can check out
the tutorial by Jerry Mendel at
http://sipi.usc.edu/~mendel/publications/FLS_Engr_Tutorial_Errata.pdf.
Note: The terminology used in this module might differ from that used in
the above tutorial.
PUBLIC METHODS
The module has the following public methods:
new()
This is the constructor. It takes no arguments, and returns an
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