Title :
A genetic algorithm for generating maximal consistent subsets from inconsistent data
Author :
Kitada, Akihiro ; Murai, Tetsuya ; Sato, Yoshiharu
Author_Institution :
Graduate Sch. of Eng., Hokkaido Univ., Sapporo, Japan
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
Keywords :
fuzzy logic; fuzzy set theory; genetic algorithms; fuzzy subsets; genetic algorithm; inconsistent data; k-partitions; maximal consistent subsets; recombination operator; Cost accounting; Data analysis; Data engineering; Fuzzy set theory; Fuzzy sets; Genetic algorithms; Postal services; State-space methods; Systems engineering and theory;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.625715
