基于正态云模型的基本概率指派生成方法及应用
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Determination of Basic Probability Assignment Based on Cloud Model and Application
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    摘要:

    基本概率指派(Basic probability assignment, BPA)生成 是应用D S证据理论的关键环节和第一步,而如何生成BPA仍然是一个有待解决的问题。本文 提出一种基于云模型的BPA生成方法,首先,采用逆向云发生器生成每类样本在某属性下的 正态云模型。其次,利用前件云发生器得到待测样本在该属性下对每类样本的确定度期望。 再次,给出一种正态云模型交叠度计算方法,用确定度最大类的正态云模型与其他种类的最 大交叠度作为对全集的信任度。最后,对确定度进行归一化得到待测样本的BPA。实验结果 验证了该方法的有效性,此外,在样本数据较少情况下也能有效生成BPA。

    Abstract:

    Determination of the basic probability assignment (BPA) is the first and main step to the evidence theory application. How to generate BPA is still an open issue. To solve the problem, a method for determining BPA based on the cloud model is proposed. Firstly, the normal cloud model of each sample under the property is constructed based on the backward cloud generator. Secondly, through the antecedent cloud generator repeatedly, the average certainty of the test sample under this property is obtained. Thirdly, a method for measuring the similarity of normal cloud models is proposed, and the maximal similarity of the normal cloud model is made, which has the maximal certainty as the belief of the universal set. Finally, the certainty is normalized to obtain the BPA of each class. The effectiveness of the method is proved by experiments, and it can generate BPA in the case of little samples numbers.

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崔家玮 李冰 李弼程.基于正态云模型的基本概率指派生成方法及应用[J].数据采集与处理,2015,30(6):1318-1324

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  • 在线发布日期: 2015-12-24