GA-Based Rule Extraction from Neural Networks for Approximation
نویسندگان
چکیده
neural networks solving approximation problem. It is based on two hierarchical evolutionary algorithms with multiobjective Pareto optimisation. The lower level algorithm searches for rules that are optimised by the upper level algorithm. The conclusion of the rule takes the form of a tree whose inner nodes contain functions and operators, and leaves—identifiers of attributes and numeric constants. The details referring to the rules encoding, genetic operators and fitness function are described. Some preliminary results of experimental studies are presented, as well.
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