Evolving complex fuzzy classifier rules using a linear tree genetic representation
作者： Dipankar Dasgupta , Fabio A. González
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摘要: The paper proposes a linear representation of tree structures in order to evolve complex fuzzy rule sets for solving classification problems. In particular, linguistic rules are evolved, where the condition part can have an arbitrary structure conjunctions and disjunctions. We describe efficient scheme, which uses genetic algorithm. method is tested with number benchmark data some results reported.
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