DocumentCode
2317364
Title
A predictor from numerical data based on fuzzy sets and rough sets
Author
Hsiao, Chih-Ching ; Ku, Yi-Wei
Author_Institution
Electr. Eng. Dept., Kao Yuan Univ., Taiwan
fYear
2010
fDate
25-27 Aug. 2010
Firstpage
139
Lastpage
144
Abstract
In this paper, we propose a fuzzy predictor which fuzzy rules are generated directly from numerical data pairs. Unfortunately, the fuzzy rules may be increase growing to extra numbers, especially the data pairs contain noise or outlier. The Fuzzy-rough feature selection will be introduced for those fuzzy rules reduction. To achieve good performance for this fuzzy predictor, the parameters of each fuzzy rule will be adjusted by fine tuning.
Keywords
fuzzy set theory; rough set theory; fuzzy predictor; fuzzy rules reduction; fuzzy sets; fuzzy-rough feature selection; rough sets;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computational Intelligence (IWACI), 2010 Third International Workshop on
Conference_Location
Suzhou, Jiangsu
Print_ISBN
978-1-4244-6334-3
Type
conf
DOI
10.1109/IWACI.2010.5585153
Filename
5585153
Link To Document