• DocumentCode
    315341
  • Title

    Constructive algorithm for neuro-fuzzy networks

  • Author

    Mascioli, F. M Frattale ; Varazi, G.M. ; Martinelli, G. M M

  • Author_Institution
    INFO-COm Dept., Rome Univ., Italy
  • Volume
    1
  • fYear
    1997
  • fDate
    1-5 Jul 1997
  • Firstpage
    459
  • Abstract
    A constructive algorithm is proposed by merging the min-max and the ANFIS models in order to obtain neuro-fuzzy networks. The min-max model is used to determine an optimal set of IF-THEN rules by following a constructive procedure. By means of this set, the architecture of an ANFIS-like net is derived with good performances in terms of structural complexity, generalization capability and speed of convergence. Simulations are described to show the behavior of the proposed algorithm
  • Keywords
    convergence; fuzzy neural nets; minimax techniques; neural net architecture; ANFIS model; IF-THEN rules; convergence; generalization capability; min-max model; neuro-fuzzy networks; optimal rule set; structural complexity; Computational efficiency; Computational modeling; Computer architecture; Computer networks; Costs; Fuzzy logic; Fuzzy neural networks; Merging; Robustness; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on
  • Conference_Location
    Barcelona
  • Print_ISBN
    0-7803-3796-4
  • Type

    conf

  • DOI
    10.1109/FUZZY.1997.616411
  • Filename
    616411