A genetic algorithm for generating maximal consistent subsets from inconsistent data

Akihiro Kitada ,Tetsuya Murai ,Yoshiharu Sato

doi:10.1109/icsmc.1997.625715

A genetic algorithm for generating maximal consistent subsets from inconsistent data

Akihiro Kitada , Tetsuya Murai + Show 1 more

https://doi.org/10.1109/icsmc.1997.625715

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Publication Date: Oct 12, 1997

Affiliation: Hokkaido University, Hokkaido Information University

#Maximal Consistent Subset #Maximal Consistent Subsets + Show 7 more

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Abstract

We developed a theory to make a formulation of fuzzy subsets and k-partitions from inconsistent data based on maximal consistent subsets developed by ourselves. To solve the most difficult point in the method of formulating fuzzy subsets from inconsistent data based on a maximal consistent subset, a genetic algorithm using a recombination operator based on the concept of forma proposed by Radcliffe (1991) is used as an extension of the usual schemata.

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