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中国管理科学 ›› 2023, Vol. 31 ›› Issue (4): 250-259.doi: 10.16381/j.cnki.issn1003-207x.2020.0614

• 论文 • 上一篇    

一种考虑形状—位置概率语言术语相似度及应用

朱峰1, 2, 刘玉敏2, 徐济超1, 苏冰杰2   

  1. 1.郑州大学管理学院,河南 郑州450001;2.郑州大学商学院,河南 郑州450001
  • 收稿日期:2020-04-07 修回日期:2020-08-06 发布日期:2023-05-06
  • 通讯作者: 刘玉敏(1956-),女(汉族),河南郑州人,郑州大学商学院,教授,博士,研究方向:决策分析、质量智能监控,Email:yuminliu@zzu.edu.cn. E-mail:yuminliu@zzu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(71672182, U1904211)

A Considering Shape—Position Probabilistic Linguistic Term Similarity and Its Application

ZHU Feng1, 2, LIU Yu-min2, XU Ji-chao1, SU Bing-jie2   

  1. 1. School of Management, Zhengzhou University,Zhengzhou 450001, China;2. School of Business, Zhengzhou University, Zhengzhou 450001, China
  • Received:2020-04-07 Revised:2020-08-06 Published:2023-05-06
  • Contact: 刘玉敏 E-mail:yuminliu@zzu.edu.cn

摘要: 为了有效测量不同概率语言术语元之间的相似程度,研究了一种考虑数据形状和位置的概率语言术语相似度。首先,通过对比不同概率语言术语元的折线图的形状,提出了概率语言术语形状相似度。其次,基于陆地移动距离(EMD)和信息完整度,定义了概率语言术语距离相似度。然后,为了测量不同概率语言术语的整体相似度,提出了考虑形状-位置的概率语言术语元的综合相似度。最后,基于改进雷达图、概率语言术语元的综合相似度和max-min算子建立了多属性决策模型,并通过算例说明所提方法的合理性和有效性。

关键词: 概率语言术语元;相似度;陆地移动距离;max-min算子;改进雷达图;多属性决策

Abstract: In order to effectively measure the similarity between different probabilistic linguistic term elements,a similarity of probabilistic linguistic term elements considering the shape and position of data is proposed. Firstly,by comparing the shapes of the scatter plots of different probabilistic linguistic term elements,the probabilistic linguistic term shape similarity is proposed. Secondly,based on the earth mover’s distance(EMD) and the completeness of the information,the distance similarity of the probabilistic linguistic term element is defined. Then,in order to measure the overall similarity of different probabilistic linguistic terms,a comprehensive similarity measure of probabilistic linguistic term element considering shape-position is proposed. Finally,a multi-attribute decision-making model is established based on improved radar graph,comprehensive similarity measure of probabilistic linguistic term element and max-min operator,and the rationality and effectiveness of the proposed method are illustrated by examples.

Key words: probabilistic linguistic term element; similarity measure; earth mover’s distance; max-min operator; improved radar graph; multi-attribute decision making

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