Self-Organizing Neuro-Fuzzy Inference System

  • Héctor Allende-Cid
  • Alejandro Veloz
  • Rodrigo Salas
  • Steren Chabert
  • Héctor Allende
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)

Abstract

The architectural design of neuro-fuzzy models is one of the major concern in many important applications. In this work we propose an extension to Rogers’s ANFIS model by providing it with a selforganizing mechanism. The main purpose of this mechanism is to adapt the architecture during the training process by identifying the optimal number of premises and consequents needed to satisfy a user’s performance criterion. Using both synthetic and real data, our proposal yields remarkable results compared to the classical ANFIS.

Keywords

ANFIS Flexible Architecture Nonlinear modeling 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Héctor Allende-Cid
    • 1
  • Alejandro Veloz
    • 1
  • Rodrigo Salas
    • 2
  • Steren Chabert
    • 2
  • Héctor Allende
    • 1
  1. 1.Dept. de InformáticaUniversidad Técnica Federico Santa MaríaValparaísoChile
  2. 2.Departamento de Ingeniería BiomédicaUniversidad de ValparaísoValparaísoChile

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