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

Module III Coactive Neuro-Fuzzy Modelling

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

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

CANFIS

CANFIS Network

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.

CANFIS & NN

CANFIS with 4 Neural rules for multiple Outputs