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CANFIS Coactive Neuro Fuzzy Inference systems

CANFIS Coactive 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.

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CANFIS Coactive Neuro Fuzzy Inference systems

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  1. CANFISCoactive 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.

  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. Multiple ANFIS

  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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