Abstract
The genotype-phenotype encoding of fuzzy rule bases in
GA, along with their corresponding crossover and
mutation operators, can be used by other search
schemes, improving the behavior of these last ones. As
a practical consequence of this, a simulated
annealing-based method for inducting both parameters
and structure of a fuzzy classifier has been developed.
The adjacency operator in SA has been replaced with a
macromutation taken from tree-shaped genotype GAs. We
will show that results of SA search are similar to
those of GP in both the efficiency of the learned
classifiers and in its linguistic interpretability,
while the memory consumption of the learning process is
lower.
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