CANFISCoactive Neuro Fuzzy Inference

systems G.Anuradha

Introduction

• Highlights the extensions of anfis

• Multiple output anfis with nonlinear fuzzy rules

• Generalized anfis is called as CANFIS

• In CANFIS both NN and FIS play an active role in a effort to reach a specific goal

Framework

• Towards multiple inputs/outputs systems

• Architectural comparisons

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.

• 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.

Multiple ANFIS

• In MANFIS no modifiable parameters are shared by the juxtaposed ANFIS models.

• Each anfis has an independent set of fuzzy rules, which makes it difficult to realize possible correlations between outputs.

• Also the adjustable parameters increases with the increase in the number of outputs