DocumentCode :
2491571
Title :
Fuzzy modeling method based on data mining
Author :
Wang, Yongfu ; Zhao, Hong ; Liu, Jiren ; Chai, Tianyou
Author_Institution :
Sch. of Mech. Eng. & Autom., Univ. of Northeastern, Shenyang
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
5223
Lastpage :
5227
Abstract :
Aiming at WM method lacking of completeness and robustness, which was presented by Lixin Wang, fuzzy system is set up by data mining in this paper. Rules base and fuzzy system produced by data mining can ergodic all the fuzzy subspace, which insures the completeness of rules base. Otherwise, rules produced by data mining are elected out in the whole sample data, but WM method is a result only from a certain datum. So, data mining has better robustness and simulation results show its validity.
Keywords :
data mining; fuzzy systems; knowledge based systems; data mining; fuzzy modeling; fuzzy system; rule based system; Association rules; Automation; Data mining; Databases; Fuzzy logic; Fuzzy sets; Fuzzy systems; Hybrid power systems; Mathematical model; Robustness; Fuzzy logic system; completeness; data mining; fuzzy rules; modelling; robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593779
Filename :
4593779
Link To Document :
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