概率逻辑
排名(信息检索)
稳健性(进化)
数学
计算机科学
人工智能
计算
相似性(几何)
功能(生物学)
语言学
机器学习
算法
进化生物学
生物
生物化学
基因
图像(数学)
哲学
化学
作者
Xingli Wu,Huchang Liao,Zeshui Xu,Arian Hafezalkotob,Francisco Herrera
标识
DOI:10.1109/tfuzz.2018.2843330
摘要
The probabilistic linguistic term set (PLTS) is a powerful technique in representing linguistic evaluations of individuals or groups in the process of decision making. The aim of this paper is to propose a strongly robust method to solve multiexperts multicriteria decision making problems with linguistic evaluations. To enrich the computation and to improve the measures of PLTS, we first define an expectation function of it. In addition, we advance three kinds of probabilistic linguistic distance measures reflecting on the difference of linguistic terms and probabilities at the same time to make up for the defects of the existing distance measures, and then propose the similarity and correlation measures. Integrating the subjective opinions with the correlation coefficients between criteria, we put forward a combined weight determining method. The robustness of the ranking method, MULTIMOORA, is enhanced by the improved Borda rule. Based on these research findings, a probabilistic linguistic MULTIMOORA method is proposed. Finally, the developed method is applied to an empirical example concerning the selection of shared karaoke television brands. The effectiveness of the proposed method is verified by some comparative analyses.
科研通智能强力驱动
Strongly Powered by AbleSci AI