一般注記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.
identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/9568
一次資料へのリンクURLhttps://dspace.jaist.ac.jp/dspace/bitstream/10119/9568/1/16017-1.pdf
著作権情報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
関連情報Integrated Uncertainty Management and Applications, Advances in Soft Computing
関連情報(DOI)10.1007/978-3-642-11960-6_26
連携機関・データベース国立情報学研究所 : 学術機関リポジトリデータベース(IRDB)(機関リポジトリ)
提供元機関・データベース北陸先端科学技術大学院大学 : JAIST学術研究成果リポジトリ