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基于证据理论的信任模型是常用的信任模型之一,且证据理论是一种具有良好理论基础的不确定性推理方法。为了解决证据收集以及冲突证据合成可能会产生不合理结果的问题,通过改进证据收集方法提高证据质量,同时结合证据距离、相似度、支持度和可信度,在证据合成过程中将冲突证据进行重新分配。实验结果表明:改进的证据合成机制提高了合成证据的合理性,使得信任计算结果更为可信。
Trust model based on evidence theory is one of the commonly used trust models, and evidence theory is a kind of uncertainty reasoning method with good theoretical foundation. In order to solve the problem that the collection of evidence and the synthesis of conflicting evidence may produce unreasonable results, the evidence quality is improved by improving the method of evidence collection. At the same time, evidence of conflict is taken into account in the process of evidence synthesis, combining the evidence distance, similarity, support and credibility Reassign. The experimental results show that the improved evidence synthesis mechanism improves the rationality of synthetic evidence and makes the confidence calculation more credible.