计算机应用 ›› 2019, Vol. 39 ›› Issue (11): 3163-3171.DOI: 10.11772/j.issn.1001-9081.2019051050

• 2019年中国计算机学会人工智能会议(CCFAI2019)论文 • 上一篇    下一篇

基于云综合方法的三支群决策模型

李帅1,2, 王国胤1, 杨洁1   

  1. 1. 计算智能重庆市重点实验室(重庆邮电大学), 重庆 400065;
    2. 南昌航空大学 数学与信息科学学院, 南昌 330063
  • 收稿日期:2019-05-24 修回日期:2019-07-19 出版日期:2019-11-10 发布日期:2019-09-11
  • 通讯作者: 王国胤
  • 作者简介:李帅(1986-),男,江西九江人,讲师,博士研究生,CCF会员,主要研究方向:粒计算、粗糙集、云模型;王国胤(1970-),男,重庆人,教授,博士,CCF会员,主要研究方向:粒计算、知识获取、认知计算、智能信息处理、大数据智能;杨洁(1987-),男,贵州遵义人,副教授,博士,CCF会员,主要研究方向:云模型、粒计算、粗糙集、机器学习。
  • 基金资助:
    国家自然科学基金资助项目(61572091,61772096);贵州省教育厅科技人才成长项目(黔科合KY[2018]318号);贵州省高层次创新型人才项目(遵科高2018[15]号);贵州省创新及探索项目(黔科合平台人才[2017年]5727-06号)。

Three-way group decisions model based on cloud aggregation

LI Shuai1,2, WANG Guoyin1, YANG Jie1   

  1. 1. Chongqing Key Laboratory of Computational Intelligence(Chongqing University of Posts and Telecommunications), Chongqing 400065, China;
    2. School of Mathematics and Information Science, Nanchang Hangkong University, Nanchang Jiangxi 330063, China
  • Received:2019-05-24 Revised:2019-07-19 Online:2019-11-10 Published:2019-09-11
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61572091, 61772096), the Science and Technology Talents Development Project of Guizhou Education Department (KY[2018]318), the High-level Innovative Talents of Guizhou Province (ZKG 2018[15]), the New Talent Cultivation Innovation and Exploration Project of Guizhou Province (QKHPTRC[2017]5727-06).

摘要: 在三支决策问题中,领域专家群决策是一种确定损失函数的最直接方法。相较于体现单一不确定性的语言变量模型和模糊集模型,云模型描述的专家评价更能够反映认知过程中复杂的不确定性形式,并能通过云综合的方法获得综合评价函数。但当前的云综合方法仅对数字特征进行简单的线性组合,缺乏对概念语义差异上的描述,难以获得令人信服的结果。因此首先证明了在云模型的距离空间中赋权距离和是一个凸函数,并将综合云模型定义为此函数的最小值点。然后,将该定义推广到多个云模型的场景下,提出了一种新的云综合方法——基于密度中心的云综合方法。群决策过程中,该方法在保证综合评价与基础评价之间的相似度最高的同时获得最精确的综合评价,为损失函数的确定提供了一种新的语义解释。实验结果表明,在与简单线性组合和合理粒度方法对比中,该方法所确定的损失函数使得三支决策中的误分类率最低。

关键词: 云综合, 云模型, 群决策, 三支决策

Abstract: Group decision making of domain experts is the most direct approach to determine loss function in three-way decision problems. Different from linguistic variable model and fuzzy set model with single uncertainty, expert evaluations described by cloud model can reflect the complex uncertainty form in cognitive process, and the synthetic evaluation function can be obtained by cloud aggregation. However, numerical characteristics only are performed simple linear combination in current cloud aggregation methods, leading the lack of the description of concept semantic differences and the difficulty to obtain convincing results. Therefore firstly, the weighted distance sum was proved to be a convex function in the distance space of cloud model. And the aggregational cloud model was defined as the minimum point of that function. Then, this definition was generalized to the multi-cloud model scenario, and a cloud aggregation method namely density center based cloud aggregation method was proposed. In group decision making, the proposed method obtains the most accurate synthetic evaluations with the highest similarity between synthetic evaluation and basic evaluation, providing a novel semantic interpretation of the determination of loss function. The experimental results show that the misclassification rate of the three-way decision with loss function determined by the proposed method is the lowest compared with simple linear combination and rational granularity methods.

Key words: cloud aggregation, cloud model, group decision making, three-way decisions

中图分类号: