QUT ePrints

A new and efficient intelligent collaboration scheme for fashion design

Yu, Yong, Choi, Tsan-Ming, Hui, Chi-Leung, & Ho, Tin Kin (2011) A new and efficient intelligent collaboration scheme for fashion design. IEEE Transactions on Systems, Man, and Cybernetics : Part A : Systems and Humans, 41(3), pp. 463-475.

View at publisher

Abstract

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance.

Impact and interest:

3 citations in Scopus
Search Google Scholar™
2 citations in Web of Science®

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

112 since deposited on 21 Apr 2011
25 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 41398
Item Type: Journal Article
Keywords: Artificial Neural Network, Design Scheme, Fuzzy Logic, Multicriteria Decision Making
DOI: 10.1109/TSMCA.2010.2089514
ISSN: 1083-4427
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Expert Systems (080105)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Decision Support and Group Support Systems (080605)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2011 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 21 Apr 2011 13:42
Last Modified: 20 Jan 2012 00:50

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page