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dc.contributor.authorKwong, C.
dc.contributor.authorFung, K.
dc.contributor.authorJiang, H.
dc.contributor.authorChan, Kit Yan
dc.contributor.authorSiu, K.
dc.date.accessioned2017-01-30T11:57:21Z
dc.date.available2017-01-30T11:57:21Z
dc.date.created2013-12-11T20:00:45Z
dc.date.issued2013
dc.identifier.citationKwong, C.K. and Fung, K.Y. and Jiang, Huimin and Chan, K.Y. and Siu, Kin Wai Michael. 2013. A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design. The Scientific World Journal. ID 636948 (11 pp.).
dc.identifier.urihttp://hdl.handle.net/20.500.11937/16727
dc.identifier.doi10.1155/2013/636948
dc.description.abstract

Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

dc.publisherHindawi Publishing Corporation
dc.titleA modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design
dc.typeJournal Article
dcterms.source.volume2013
dcterms.source.startPage1
dcterms.source.endPage12
dcterms.source.issn1537-744X
dcterms.source.titleThe Scientific World Journal
curtin.note

This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/ Please refer to the licence to obtain terms for any further reuse or distribution of this work.

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curtin.accessStatusOpen access


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