DocumentCode
3725315
Title
Extreme Learning ANFIS for classification problems
Author
Abhinav Tushar; Abhinav;G. N. Pillai
Author_Institution
Department of Electrical Engineering, Indian Institute of Technology, Roorkee, India
fYear
2015
Firstpage
784
Lastpage
787
Abstract
This paper compares Extreme Learning ANFIS (ELANFIS) with conventional ANFIS for classification problems. ELANFIS is a hybrid Fuzzy System based on Extreme Learning Machines. It combines the linguistic knowledge representation of a Fuzzy System with the fast learning speed of ELMs. This paper also proposes the use of a zero order ELANFIS for classification tasks and compares it with first order Fuzzy Systems. The results show that zero order ELANFIS gives lesser classification error with faster learning speed as compared to the mentioned methods since the number of parameters to tune is lesser.
Keywords
"Training","Fuzzy systems","Fuzzy logic","Yttrium","Mathematical model","Input variables","Next generation networking"
Publisher
ieee
Conference_Titel
Next Generation Computing Technologies (NGCT), 2015 1st International Conference on
Type
conf
DOI
10.1109/NGCT.2015.7375227
Filename
7375227
Link To Document