DocumentCode
3374007
Title
A SVR-based Fuzzy System
Author
Tian, Xianzhong ; Hu, Tongsen
Author_Institution
Inf. Eng. Coll., Zhejiang Univ. of Technol., Hangzhou
Volume
2
fYear
2006
fDate
20-24 June 2006
Firstpage
483
Lastpage
487
Abstract
This paper builds a SVR-based fuzzy system, which is combined by support vector machine and fuzzy system. Every rule corresponds to a small SVR, and subjection degree of every rule is obtained automatically from a neural network. It overcomes the disadvantage of manual-decided subjection degree in advance. From emulation test, we can see that it is a high accuracy and high effect system
Keywords
fuzzy set theory; fuzzy systems; learning (artificial intelligence); neural nets; regression analysis; support vector machines; SVR-based fuzzy system; manual-decided subjection degree; neural network; support vector machine; Arithmetic; Educational institutions; Emulation; Fuzzy systems; Input variables; Learning systems; Neural networks; Statistical learning; Support vector machines; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on
Conference_Location
Hanzhou, Zhejiang
Print_ISBN
0-7695-2581-4
Type
conf
DOI
10.1109/IMSCCS.2006.172
Filename
4673753
Link To Document