一种基于云模型和证据理论的融合识别方法

A Fusion Recognition Method Based on Cloud Model and Evidence Theory

  • 摘要: 针对目标特征参数具有不同数据类型而不易识别的问题,提出一种基于云模型和D-S证据理论的目标特征参数建模与融合识别方法.该方法首先利用云模型对数字信息和语义信息进行统一建模,从而获得测量参数的隶属度;然后将隶属度转化为基本概率赋值;最后利用证据理论融合处理得出决策结果.仿真结果表明所提的方法是有效的,其既能处理参数为单值或单区间值的情况,也能处理参数为多值或多区间值的情况.

     

    Abstract: Motivated by the problem that the characteristic of target parameters with different data types is not easy to identify, a type of target characteristic parameter modeling and fusion recognition method is proposed based on a cloud model and the D-S evidence theory. First, to obtain the membership, digital and semantic data are combined by a cloud model in this method. Then, the membership is transferred to the basic probability assignment, and decision information is derived using the evidence theory. Finally, simulation experiment is conducted to prove the effectiveness of the proposed method. The simulation results show that the method can process both single-or single-interval value parameters as well as multiple-or multiple-interval-value parameters.

     

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