Title :
A SVR-based Fuzzy System
Author :
Tian, Xianzhong ; Hu, Tongsen
Author_Institution :
Inf. Eng. Coll., Zhejiang Univ. of Technol., Hangzhou
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;
Conference_Titel :
Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on
Conference_Location :
Hanzhou, Zhejiang
Print_ISBN :
0-7695-2581-4
DOI :
10.1109/IMSCCS.2006.172
