[1]张文德 李燕园.基于证据理论和中智集的不确定数据融合方法研究[J].信息化理论与实践,2021,(01):85-91.
　Zhang Wen-de Li yan-yuan.Research on Uncertain Data Fusion Method Based on Evidence Theory and Neutrosophic Sets[J].Information Theory and Practice,2021,(01):85-91.
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基于证据理论和中智集的不确定数据融合方法研究()
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《信息化理论与实践》[ISSN:2520-5862/CN:]

卷:
期数:
2021年01
页码:
85-91
栏目:
出版日期:
2021-12-31

文章信息/Info

Title:
Research on Uncertain Data Fusion Method Based on Evidence Theory and Neutrosophic Sets
作者:
张文德 李燕园
福州大学信息管理研究所
Author(s):
Zhang Wen-de Li yan-yuan
(Information Management Institute, Fuzhou University, Fuzhou 350108, China)
关键词:
多属性群决策; 数据融合; 证据理论; 单值中智集; 中智熵
Keywords:
Multiple Attribute Group Decision Making;  Data Fusion;  Evidence Theory;  Single- valued Neutrosophic set;  Entropy of Neutrosophic set s
摘要:
目的]针对多属性群决策中的不确定数据融合问题，提出基于证据理论和中智集的不确定数据融合方法。[方法]首先，利用中智信息熵确定属性数据权重，并将专家对各属性的以单值中智数形式表示的评价数据转化为基本概率分配函数形式，利用D-S证据合成公式将专家关于方案集的多属性证据进行融合。然后，利用证据冲突度度量不同专家之间的评价数据的冲突程度并确定各专家权重，再利用D-S证据合成公式将所有专家关于方案集的数据进行融合。[结果]从智慧校园背景下的智慧教室建设方案选择场景中提炼具体问题，通过实例进行验证分析。[局限]中智环境下的D-S证据合成公式及基本概率分配函数的构造有待进一步优化与完善。[结论]本文所提出的方法具有一定的合理性与有效性。
Abstract:
[Objective]Aiming at the problem of uncertain data fusion in multi-attribute group decision making, an uncertain data fusion method based on evidence theory and intelligence set is proposed.[Methods]Firstly,the weight of attribute data is determined by using Chinese intelligence information entropy, and the evaluation data of each attribute in the form of single valued Chinese intelligence number is transformed into the form of basic probability distribution function, and the multi-attribute evidence of experts about the scheme set is fused by using D-S evidence synthesis formula. Then,the conflict degree of evidence is used to measure the conflict degree of evaluation data among different experts, and the weight of each expert is determined.Then, the D-S evidence synthesis formula is used to fuse the data of all experts about the scheme set.[Results]The specific problems were extracted from the scenario of smart classroom construction scheme selection under the background of smart campus,and verified and analyzed by examples.[Limitation]The construction of D-S evidence composition formula and basic probability distribution function in Chinese intelligence environment needs to be further optimized and improved.[Conclusion]The method proposed in this paper is reasonable and effective

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更新日期/Last Update: 2022-12-20