• DocumentCode
    2181462
  • Title

    Research on Product Image Form Design Based on ANFIS

  • Author

    Li, Yongfeng ; Zhu, Liping

  • Author_Institution
    Coll. of Mech. & Electr. Eng., Xuzhou Normal Univ., Xuzhou, China
  • Volume
    1
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    119
  • Lastpage
    122
  • Abstract
    Product image form design, which focuses on customers´ psychological demands, is arousing attention increasingly. This paper presents a novel approach of customer-oriented design for translating customers´ kansei image into product design elements. The most influential form elements are identified through rough set theory. Based on this, the relationship between the key form elements and customers´ kansei is constructed by adaptive neuro-fuzzy inference system (ANFIS) using MATLAB. To validate the prediction performance of ANFIS, fuzzy logic and back propagation neural network models are utilized. An experimental study of glasses design is conducted based on the proposed method, and the results suggest that ANFIS has a good prediction performance.
  • Keywords
    backpropagation; customer satisfaction; demand forecasting; design; fuzzy logic; fuzzy reasoning; production engineering computing; rough set theory; ANFIS; Matlab; adaptive neuro-fuzzy inference system; back propagation neural network; customer-oriented design; customers psychological demands; fuzzy logic; kansei image; product image form design; rough set theory; Adaptation model; Artificial neural networks; Firing; Fuzzy logic; Glass; Predictive models; Product design; ANFIS; glasses; kansei engineering; product design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design (ISCID), 2010 International Symposium on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-8094-4
  • Type

    conf

  • DOI
    10.1109/ISCID.2010.46
  • Filename
    5692678