• DocumentCode
    510050
  • Title

    Applying Neural Networks to Consumer-Oriented Product Design

  • Author

    Lin, Yang-Cheng ; Yeh, Chung-Hsing ; Wang, Chen-Cheng

  • Author_Institution
    Dept. of Arts & Design, Nat. Dong Hwa Univ., Hualien, Taiwan
  • Volume
    2
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    497
  • Lastpage
    502
  • Abstract
    How to create highly-reputable designs and hot-selling products is an essential issue on product design. This paper presents an experimental study to explore the relationship between the consumers´ perceptions and product form elements, using one linear quantitative technique (i.e. the grey model) and one nonlinear quantitative technique (i.e. the neural network model). Thirty representative personal digital assistants (PDAs) and six design form elements of PDAs are identified as samples in an experimental study to illustrate how these techniques work. The performance evaluation result shows that the NN model is better to be used to construct a form design database for helping product designers comprehend consumers´ perceptions, thus supporting form design decisions in a new PDA product development process.
  • Keywords
    consumer behaviour; grey systems; neural nets; notebook computers; performance evaluation; product design; product development; PDA product development process; consumer perceptions; consumer-oriented product design; design form elements; form design database; grey model; highly-reputable designs; hot-selling products; neural networks; nonlinear quantitative technique; performance evaluation; personal digital assistants; product form elements; Art; Artificial intelligence; Artificial neural networks; Computational intelligence; Design engineering; Differential equations; Information technology; Neural networks; Personal digital assistants; Product design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.478
  • Filename
    5375884