基于灰色关联分析和D-S证据理论的区间直觉模糊决策方法

李鹏; 刘思峰

doi:10.3724/SP.J.1004.2011.00993

基于灰色关联分析和D-S证据理论的区间直觉模糊决策方法

doi: 10.3724/SP.J.1004.2011.00993

李鹏^,,
刘思峰

1.
南京航空航天大学经济与管理学院南京 210016

详细信息

通讯作者:
李鹏南京航空航天大学经济与管理学院博士研究生. 主要研究方向为决策分析与灰色系统理论.本文通信作者.E-mail: jellyok@126.com

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出版历程
- 收稿日期: 2010-10-25
- 修回日期: 2011-02-18
- 刊出日期: 2011-08-20

Interval-valued Intuitionistic Fuzzy Numbers Decision-making Method Based onGrey Incidence Analysis and D-S Theory of Evidence

LI Peng^,,
LIU Si-Feng

1.
College of Economics and Manangement, Nanjing University of Aeronautics and Astronautics, Nanjing 210016

摘要

摘要: 针对方案的指标值为区间直觉模糊数的决策问题,提出了一种基于灰色关联分析和D-S证据理论的决策方法. 定义了区间记分函数和区间数点算子, 并通过其将区间直觉模糊数转化为记分函数;利用记分函数以及灰色关联方法确定各指标的不确信度, 进而构建出不同指标下各方案的Mass函数, 通过D-S合成法则进行信息融合,确定最优方案.最后,通过算例表明, 本文提出的方法可得到满意结果并显著降低决策的不确定性.
- 区间直觉模糊数 /
- D-S证据理论 /
- 数据融合 /
- 决策 /
- 灰色关联分析
Abstract: A method based on grey incidence analysis and D-S theory of evidence is proposed for decision-making problems with the attribute values of corresponding alternatives in the form of interval-valued intuitionistic fuzzy numbers. The uncertain degrees of different indices are determined by using the grey incidence analysis. First, the concept of interval-valued score function and interval number point operators are introduced, and the interval-valued intuitionistic fuzzy numbers are transformed into score function by them. The uncertain degrees of different indices are determined by using the grey incidence analysis and score functions, and the mass functions of different alternatives in different indices are obtained by the uncertain degrees and score functions. Information can be fused in accordance with the D-S combination rule and the best alternative is got by using the method. Finally, a numerical example is utilized to illustrate that a satisfying conclusion can be obtained and an obvious decrease can be observed in the uncertainty of decision making.
- Interval-valued intuitionistic fuzzy numbers /
- D-S theory of evidence /
- data fusion /
- decision-making /
- grey incidence analysis

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参考文献(1)

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