Extreme Learning ANFIS for classification problems
- Resource Type
- Conference
- Authors
- Tushar, Abhinav; Abhinav; Pillai, G. N.
- Source
- 2015 1st International Conference on Next Generation Computing Technologies (NGCT) Next Generation Computing Technologies (NGCT), 2015 1st International Conference on. :784-787 Sep, 2015
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Training
Fuzzy systems
Fuzzy logic
Yttrium
Mathematical model
Input variables
Next generation networking
Fuzzy inference system
ANFIS
Extreme Learning ANFIS
Classification
ELM
- Language
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.