A hybrid Kansei engineering system using the self-organizing map neural network

The, C. S. and Lim, Chee Peng 2007, A hybrid Kansei engineering system using the self-organizing map neural network, Journal of IT in Asia, vol. 2, no. 1, pp. 23-38.

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Title A hybrid Kansei engineering system using the self-organizing map neural network
Author(s) The, C. S.
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Journal name Journal of IT in Asia
Volume number 2
Issue number 1
Start page 23
End page 38
Total pages 16
Publisher Unit Penerbitan Universiti Malaysia Sarawak
Place of publication Sarawak, Malaysia
Publication date 2007
ISSN 1823-5042
Keyword(s) decision support system
Kansei engineering
self-organizing map
interior design
Summary Kansei Engineering (KE), a technology founded in Japan initially for product design, translates human feelings into design parameters. Although various intelligent approaches to objectively model human functions and therelationships with the product design decisions have been introduced in KE systems, many or the approaches are not able to incorporate human subjective feelings and preferenees into the decision-making process. This paper proposes a new hybrid KE system that attempts to make the machine-based decision-making process closely resembles the real-world practice. The proposed approach assimilates human perceptive and associative abililities into the decision-making process of the computer. A number of techniques based on the Self-Organizing Map (SOM) neural network are employed in the backward KE system to reveal the underlying data structures that are involved in the decision-making process. A case study on interior design is presented to evaluate the efficacy of the proposed approach. The results obtained demonstrate tbe effectiveness of the proposed approach in developing an intelligent KE system which is able to combine huiiUUI feelings and preferences into its decision making process.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2007, Unit Penerbitan Universiti Malaysia Sarawak
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048647

Document type: Journal Article
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