Canfis

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Canfis

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Canfis

  1. 1. CANFIS Coactive Neuro Fuzzy Inference systems G.Anuradha
  2. 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. 3. Framework • Towards multiple inputs/outputs systems • Architectural comparisons
  4. 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.
  5. 5. • 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.
  6. 6. Multiple ANFIS
  7. 7. • 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

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