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
Link To Document :
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