1. Dr. Unnikrishnan P.C. Professor, EEE
EE368 Soft Computing
Dr. Unnikrishnan P.C.
Professor, EEE

2. Module III
Coactive Neuro-Fuzzy Modelling

3. Introduction CANFIS belongs to a more general class of ANFIS
Highlights the extensions of ANFIS
Multiple output ANFIS with nonlinear fuzzy rules
In CANFIS both NN and FIS play an active role in a effort to reach a specific goal
Their mutual dependence presents unexpected learning capabilities

4. Towards multiple inputs/outputs systems
CANFIS has extended the notion of single output system of ANFIS to produce multiple outputs.
One way to accomplish is to place as many ANFIS models side by side as the number of required outputs.
CANFIS yields advantage from nonlinear fuzzy rules

5. CANFIS

6. CANFIS Network

7. CANFIS …..
In CANFIS the antecedents are the same, but the consequents are different according the number of outputs required.
Fuzzy rules are constructed with shared membership values to express correlations between outputs.

8. CANFIS & NN

9. CANFIS with 4 Neural rules for multiple Outputs