Canfis

1. CANFIS
Coactive Neuro Fuzzy Inference
systems
G.Anuradha

2. 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

3. Framework
• Towards multiple inputs/outputs systems
• Architectural comparisons

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.

6. • 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.

7. Multiple ANFIS

8. • 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