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A generalized golden rule representative value for multiple-criteria decision analysis
Citation
Liu, Z and Xiao, F and Lin, C-T and Kang, BH and Cao, Z, A generalized golden rule representative value for multiple-criteria decision analysis, IEEE Transactions on Systems, Man, and Cybernetics: Systems pp. 1-12. ISSN 2168-2216 (2019) [Refereed Article]
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Copyright Statement
Copyright 2019 IEEE.
DOI: doi:10.1109/TSMC.2019.2919243
Abstract
Multicriteria decision analysis evaluates multiple conflicting criteria in decision making, but conflicting criteria are typical in evaluating options. As the existing ordering operations involved in multicriteria decision making cannot easily be implemented with intervals, we assume that scalar representative values with intervals can effectively avoid this issue. To deal with interval-valued criteria, we propose a generalized golden rule representative value approach, which involves the sigmoid function of backpropagation neural networks to tune parameters. Our approach considers the uncertainties and side effects of the interval variables to improve individual scalar representative values. Based on numerical examples, we address the effectiveness of the proposed approach, and we provide a specific application concerning multicriteria decision making with interval criteria satisfaction.
Item Details
Item Type: | Refereed Article |
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Keywords: | comparison system, golden rule representative value, interval valued, multicriteria decision function, sigmoid function, uncertainty, uzzy rule |
Research Division: | Information and Computing Sciences |
Research Group: | Machine learning |
Research Field: | Neural networks |
Objective Division: | Defence |
Objective Group: | Defence |
Objective Field: | Intelligence, surveillance and space |
UTAS Author: | Kang, BH (Professor Byeong Kang) |
UTAS Author: | Cao, Z (Dr Zehong Cao) |
ID Code: | 133136 |
Year Published: | 2019 |
Web of Science® Times Cited: | 11 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2019-06-13 |
Last Modified: | 2020-05-18 |
Downloads: | 23 View Download Statistics |
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