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 :
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