RANFIS Rough Adaptive Neuro-Fuzzy Inference System
| Main Authors: | Sandeep Chandana, Rene V. Mayorga |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2007
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1078279 |
Daftar Isi:
- The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.