Adaptive neuro fuzzy inference system

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Adaptive neuro fuzzy inference system (ANFIS) is a kind of artificial neural network that is based on Takagi–Sugeno fuzzy inference system. Since it integrates both neural networks and fuzzy logic principles, it has potential to capture the benefits of both in a single framework. Its inference system corresponds to a set of fuzzy IF–THEN rules that have learning capability to approximate nonlinear functions.[1] Hence, ANFIS is considered to be a universal estimator.[2]

References[edit]

  1. ^ Nedjah, Nadia (ed.). "Adaptation of Fuzzy Inference System Using Neural Learning, Fuzzy System Engineering: Theory and Practice". Studies in Fuzziness and Soft Computing (Germany: Springer Verlag): 53–83. ISBN 3-540-25322-X. 
  2. ^ Jang, Sun, Mizutani (1997) – Neuro-Fuzzy and Soft Computing – Prentice Hall, pp 335–368, ISBN 0-13-261066-3

3. Tahmasebi, P., Hezarkhani, A., Application of Adaptive Neuro-Fuzzy Inference System for Grade Estimation. http://www.ajbasweb.com/ajbas/2010/408-420.pdf[dead link]