• DocumentCode
    295873
  • Title

    Coactive neuro-fuzzy modelling for colour recipe prediction

  • Author

    Mizutani, Eiji ; Jang, Jyh-Shing R. ; Nishio, Kcnichi ; Takagi, Hideyuki ; Anslander, D.M.

  • Author_Institution
    Inf. Syst. Dept., Kansai Paint Co. Ltd., Osaka, Japan
  • Volume
    5
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    2252
  • Abstract
    Explores neuro-fuzzy approaches to computerized colour recipe prediction which relates surface spectral reflectance of a target colour to several colorant proportions. The approaches are expressed within the framework of CANFIS (co-active neuro-fuzzy inference system) where both neural networks (NNs) and fuzzy systems (FSs) play active roles together in pursuit of a given task. To find an ideal adaptive model for this problem, the authors have investigated a variety of structures, they feature knowledge-embedded architectures and an adaptive FS, which serves to determine colour selection. They have enormous potential for augmenting prediction capability
  • Keywords
    colour; fuzzy systems; knowledge based systems; neural nets; reflectivity; CANFIS; coactive neuro-fuzzy modelling; colorant proportions; colour recipe prediction; colour selection; knowledge-embedded architectures; surface spectral reflectance; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.487712
  • Filename
    487712