Title :
Robust function approximation based on fuzzy sets and rough sets
Author :
Hsiao, Chih-Ching
Author_Institution :
Electr. Eng. Dept., Kao Yuan Univ., Kaohsiung, Taiwan
Abstract :
The rough set theory is successes to deal with imprecise, incomplete or uncertain for information system. Fuzzy set and the rough set theories turned out to be particularly adequate for the analysis of various types of data, especially, when dealing with inexact, uncertain or vague knowledge. In this paper, we propose an novel algorithm, which termed as rough-fuzzy c-regression model (RFCRM), that define fuzzy subspaces in a fuzzy regression manner and also include rough-set theory for TSK modeling with robust capability against outliers.
Keywords :
function approximation; fuzzy set theory; regression analysis; rough set theory; TSK modeling; fuzzy set theory; robust function approximation; rough set theory; rough-fuzzy c-regression model; Clustering algorithms; Degradation; Function approximation; Fuzzy sets; Least squares approximation; Robustness; Rough sets; Set theory; Training data; Working environment noise;
Conference_Titel :
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location :
Jeju Island
Print_ISBN :
978-1-4244-3596-8
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2009.5277427
