D
Dong-Ling Xu
Researcher at University of Manchester
Publications - 178
Citations - 9132
Dong-Ling Xu is an academic researcher from University of Manchester. The author has contributed to research in topics: Evidential reasoning approach & Multiple-criteria decision analysis. The author has an hindex of 44, co-authored 166 publications receiving 7692 citations. Previous affiliations of Dong-Ling Xu include Chinese Ministry of Education & Hefei University of Technology.
Papers
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Journal ArticleDOI
On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty
Jian-Bo Yang,Dong-Ling Xu +1 more
TL;DR: The fundamental features of the ER approach are investigated and new schemes for weight normalization and basic probability assignments are proposed to enhance the process of aggregating attributes with uncertainty.
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Evidential reasoning rule for evidence combination
Jian-Bo Yang,Dong-Ling Xu +1 more
TL;DR: The ER rule completes and enhances [email protected]?s rule by identifying how to combine pieces of fully reliable evidence that are highly or completely conflicting through a new reliability perturbation analysis.
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Environmental impact assessment using the evidential reasoning approach
TL;DR: The ER approach will be used to aggregate multiple environmental factors, resulting in an aggregated distributed assessment for each alternative policy, and a new analytical ER algorithm will be investigated which provides a means for using the ER approach in decision situations where an explicit ER aggregation function is needed.
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On the centroids of fuzzy numbers
TL;DR: This paper presents the correct centroid formulae for fuzzy numbers and justify them from the viewpoint of analytical geometry and a numerical example demonstrates that Cheng's formULae can significantly alter the result of the ranking procedure.
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The evidential reasoning approach for MADA under both probabilistic and fuzzy uncertainties
TL;DR: In this article, a utility-based grade match method is proposed to transform both numerical data and qualitative (fuzzy) assessment information of various formats into the fuzzy belief structure, leading to a fuzzy belief decision matrix.