Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/27482
DC Field | Value | Language |
---|---|---|
dc.contributor | School of Design | - |
dc.contributor | Department of Industrial and Systems Engineering | - |
dc.creator | Kwong, CK | - |
dc.creator | Fung, KY | - |
dc.creator | Jiang, H | - |
dc.creator | Chan, KY | - |
dc.creator | Siu, KWM | - |
dc.date.accessioned | 2015-06-23T09:17:07Z | - |
dc.date.available | 2015-06-23T09:17:07Z | - |
dc.identifier.issn | 2356-6140 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/27482 | - |
dc.language.iso | en | en_US |
dc.publisher | Hindawi Publishing Corporation | en_US |
dc.rights | Copyright © 2013 C. K. Kwong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_US |
dc.rights | The following article: C. K. Kwong, K. Y. Fung, Huimin Jiang, K. Y. Chan, and Kin Wai Michael Siu, “A Modified Dynamic Evolving Neural-Fuzzy Approach to Modeling Customer Satisfaction for Affective Design,” The Scientific World Journal, vol. 2013, Article ID 636948, 11 pages, 2013, is available at https://doi.org/10.1155/2013/636948 | en_US |
dc.title | A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 2013 | en_US |
dc.identifier.doi | 10.1155/2013/636948 | en_US |
dcterms.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. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | The scientific world journal, 2013, v. 2013, 636948 | - |
dcterms.isPartOf | The scientific world journal | - |
dcterms.issued | 2013 | - |
dc.identifier.isi | WOS:000328790200001 | - |
dc.identifier.scopus | 2-s2.0-84893835337 | - |
dc.identifier.pmid | 24385884 | - |
dc.identifier.eissn | 1537-744X | en_US |
dc.identifier.rosgroupid | r71336 | - |
dc.description.ros | 2013-2014 > Academic research: refereed > Publication in refereed journal | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Kwong_modified_dynamic_evolving.pdf | 4.4 MB | Adobe PDF | View/Open |
Page views
113
Last Week
1
1
Last month
Citations as of Apr 21, 2024
Downloads
88
Citations as of Apr 21, 2024
SCOPUSTM
Citations
8
Last Week
0
0
Last month
0
0
Citations as of Apr 19, 2024
WEB OF SCIENCETM
Citations
7
Last Week
0
0
Last month
0
0
Citations as of Apr 18, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.