DocumentCode
1750933
Title
Learning rules approach to R-FNN
Author
Wen, Mo Zhi ; Dan, Hu ; Lan, Shu
Author_Institution
Dept. of Math., Sichuan Normal Univ., Chengdu, China
Volume
2
fYear
2001
fDate
25-28 July 2001
Firstpage
639
Abstract
With the help of rough set theory, the paper puts forward a novel way of machine learning: LBR (learning by rough set). Base on this new algorithm, we can design a modal of R-FNN (rough-fuzzy neural network). The presentation of this new modal provides us with an intellectual approach to deal with data. Through practice in forecasting, the R-FNN has a good effect
Keywords
fuzzy neural nets; fuzzy set theory; learning (artificial intelligence); rough set theory; LBR; R-FNN; intellectual approach; learning by rough set; learning rule approach; machine learning; modal; rough set theory; rough-fuzzy neural network; Algorithm design and analysis; Bismuth; Fuzzy neural networks; Fuzzy set theory; Fuzzy sets; Humans; Neural networks; Neurons; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-7078-3
Type
conf
DOI
10.1109/NAFIPS.2001.944677
Filename
944677
Link To Document