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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/9568

Title: Linguistic Multi-Expert Decision Making Involving Semantic Overlapping
Authors: Yan, Hong-Bin
Huynh, Van-Nam
Nakamori, Yoshiteru
Keywords: Multi-expert decision making
Linguistic assessments
Aggregation
Target-oriented ranking
Issue Date: 2010-03-26
Publisher: Springer
Magazine name: 
Volume: 68/2010
Start page: 281
End page: 292
DOI: 10.1007/978-3-642-11960-6_26
Abstract: This paper presents a probabilistic model for linguistic multi-expert decision making (MEDM), which is able to deal with vague concepts in linguistic aggregation and decision-makers’ preference information in choice function. In linguistic aggregation phase, the vagueness of each linguistic judgement is captured by a possibility distribution on a set of linguistic labels. A confidence parameter is also incorporated into the basic model to model experts’ confidence degree. The basic idea of this linguistic aggregation is to transform a possibility distribution into its associated probability distribution. The proposed linguistic aggregation results in a set of labels having a probability distribution. As a choice function, a target-oriented ranking method is proposed, which implies that the decision-maker is satisfactory to choose an alternative as the best if its performance is as at least “good” as his requirements.
Rights: This is the author-created version of Springer, Hong-Bin Yan, Van-Nam Huynh and Yoshiteru Nakamori, Integrated Uncertainty Management and Applications, Advances in Soft Computing, 68/2010, 2010, 281-292. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-642-11960-6_26
URI: http://hdl.handle.net/10119/9568
Material Type: author
Appears in Collections:a10-2. 図書 (Book, Book Chapter)

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