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    杜思伟, 林家骏. 适用于信息融合算法性能评估的DS改进算法[J]. 华东理工大学学报(自然科学版), 2011, (6): 745-748.
    引用本文: 杜思伟, 林家骏. 适用于信息融合算法性能评估的DS改进算法[J]. 华东理工大学学报(自然科学版), 2011, (6): 745-748.
    DU Si-wei, LIN Jia-jun. An Improved DS Evidence Combination Algorithm Applied to Information Fusion Algorithm Performance Evaluation[J]. Journal of East China University of Science and Technology, 2011, (6): 745-748.
    Citation: DU Si-wei, LIN Jia-jun. An Improved DS Evidence Combination Algorithm Applied to Information Fusion Algorithm Performance Evaluation[J]. Journal of East China University of Science and Technology, 2011, (6): 745-748.

    适用于信息融合算法性能评估的DS改进算法

    An Improved DS Evidence Combination Algorithm Applied to Information Fusion Algorithm Performance Evaluation

    • 摘要: 为了解决信息融合算法管理过程中的最优算法决策问题,引入DempsterShafer证据理论。针对在实际应用过程中,由于相关证据合成而出现的评估结果超估计现象,提出了一种改进的证据合成方法。通过建立不同指标之间的相关性度量函数,对相关证据的基本概率赋值进行相应的调整,对修正后的证据再进行证据组合。实验结果验证了所提方法的合理有效性。

       

      Abstract: The DempsterShafer evidence theory is introduced to decide the optimal algorithm for information fusion management. Moreover, an improved evidence combination approach is proposed such that the overestimate generated from the combination of relevant evidence is suppressed. The relevance measurement function is generated and the basic probability assignment of the relevant evidences is adjusted. And then, the revised evidence is further combined. A numerical example provided shows the rationality and efficiency of the proposed approach.

       

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