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中文摘要：
证据的不确定性从根本上影响到融合结果,目前证据理论中还没有完善的不确定性度量方法。针对D-S证据理论在合成高冲突证据时会得到有悖常理的结果的问题,许多学者提出了修正证据源的改进方法,但是这些方法大多没有考虑到证据的不确定性问题。模糊熵方法是一种非常有效的模糊性（不确定性）的测度方法。考虑到证据的不确定性,本文提出一种新的基于证据距离和模糊熵的加权证据融合方法,该方法利用模糊熵方法计算各个证据的不确定度系数,修正基于证据距离的各证据源的权重,得到各证据源的综合权重。实验结果证明了本文方法的有效性。
英文摘要：
The evidence ambiguity can fundamentally affect the fusion results, but no impeccable method has been found to measure the evidence ambiguity in evidence theory. To suppress the counterintuitive results generated in the combination of high conflicting evidences, many scholars have proposed modified combination approaches based on the correction of original evidence. However, these methods do not take evidence ambiguity into consideration. Fuzzy entropy method can effectively evaluate the ambiguity （uncertainty）. Given the evidence uncertainty, this paper proposes a new weighted evidence fusion algorithm based on evidence distance and fuzzy entropy theory. The coefficients of uncertainty of each evidence can be obtained by the fuzzy entropy method. Then, the weights acquired by evidence distance are amended by the coefficients of uncertainty to obtain the synthesis weights. The obtained results show the effective results of the proposed method.
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