Title :
Mutually-inversistic rough fuzzy logic
Author_Institution :
Inst. of Inf. Technol., Beijing Union Univ., Beijing, China
Abstract :
Mutually-inversistic rough fuzzy logic is the integration of mutually-inversistic fuzzy logic constructed by the author and rough fuzzy sets. Mutually-inversistic fuzzy logic can be used to mine fuzzy association rules on the finer granule objects, while mutually-inversistic rough fuzzy logic can be used to mine fuzzy association rules on the coarser granule equivalence classes.
Keywords :
data mining; fuzzy logic; granular computing; rough set theory; fuzzy association rule mining; granule equivalence class; mutually inversistic rough fuzzy logic; rough fuzzy sets; Approximation methods; Association rules; Employment; Fuzzy logic; Fuzzy sets; Materials; Rain; fuzzy association rule mining of the lower and upper approximations of equivalence classes; granular computing; mutually-inversistic fuzzy logic; mutually-inversistic rough fuzzy logic; rough fuzzy sets;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
DOI :
10.1109/FSKD.2011.6019505
