• DocumentCode
    1917570
  • Title

    Enhancing multi-neural systems through the use of hybrid structures

  • Author

    Canuto, Anne M P ; Fairhurst, Michael ; Howells, Gareth

  • Author_Institution
    Informatics & Appl. Mathematic Dept., Univ. Fed. do Rio Grande do Norte, Natal, Brazil
  • Volume
    1
  • fYear
    2003
  • fDate
    20-24 July 2003
  • Firstpage
    316
  • Abstract
    This paper investigates the performance of multi-neural systems, focusing on the benefits that can be gained when integrating different types of neural experts (hybrid multi-neural system). An empirical evaluation shows that the integration of different types of neural networks leads to an improvement in performance in a practical classification task for a range of combination methods.
  • Keywords
    fuzzy neural nets; learning (artificial intelligence); multilayer perceptrons; pattern classification; classification task; fuzzy neural networks; hybrid structures; multi-neural combination; multineural systems; neural experts; Data analysis; Electronic mail; Fuzzy neural networks; Informatics; Mathematics; Multi-layer neural network; Multilayer perceptrons; Neural networks; Pattern recognition; Performance analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2003. Proceedings of the International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7898-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2003.1223364
  • Filename
    1223364