In recent years, the Dempster–Shafer Theory (DST) has been widely applied in areas such as target classification and multi-modal fusion due to its advantages in uncertain reasoning. However, in DST, when there exists highly conflicts between Sources of Evidence (SoEs), it often leads to counterintuitive fusion results, thereby affecting the performance of the final fused decision-making. To eliminate the potential impact of highly conflicts during the fusion process, this paper primarily focuses on modifying the SoEs themselves to achieve the discounting fusion. Currently, existing literature has proposed numerous discounting fusion methods to address highly conflict fusion. However, in these discounting strategies, the determination of discounting factors is typically based on a single criterion. Considering that a single indicator cannot comprehensively and accurately assess the reliability of each evidence source, this paper introduces a novel conflict evidence combination method based on a multi-criteria evaluation strategy. In this method, the Best and Worst Method (BWM) is initially used to prioritize the best SoE, determining the solution points for each criterion and subsequently selecting the ideal solution. Then, combining the selected criteria: distance, relative entropy, and divergence metrics, reliability calculation is performed based on the Stable Preference Order Theory for Ideal Solution (SPOTIS), which achieves a stable preference order strategy towards the ideal solutions. Finally, leveraging the discounting fusion method in DST, modification and fusion of the original highly conflict SoEs are achieved. Through extensive experiments, the effectiveness and practicality of the proposed method in this paper have been validated.

中文翻译：

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一种新颖的多准则冲突证据组合方法及其在模式识别中的应用

近年来，登普斯特-谢弗理论（DST）因其在不确定性推理方面的优势而在目标分类、多模态融合等领域得到广泛应用。然而，在DST中，当证据来源（SoE）之间存在高度冲突时，往往会导致违反直觉的融合结果，从而影响最终融合决策的性能。为了消除融合过程中高度冲突的潜在影响，本文主要关注对SoE本身的修改以实现贴现融合。目前，现有文献提出了多种折扣融合方法来解决高度冲突的融合。然而，在这些折扣策略中，折扣因子的确定通常基于单一标准。考虑到单一指标无法全面、准确地评估各个证据来源的可靠性，提出一种基于多标准评价策略的冲突证据组合方法。在此方法中，首先使用最佳和最差方法 (BWM) 来确定最佳 SoE 的优先级，确定每个标准的解决方案点，然后选择理想的解决方案。然后，结合选定的标准：距离、相对熵和散度度量，基于理想解的稳定偏好顺序理论（SPOTIS）进行可靠性计算，实现了朝向理想解的稳定偏好顺序策略。最后，利用DST中的贴现融合方法，实现了对原有高度冲突的SoE的修改和融合。通过大量的实验，验证了本文提出的方法的有效性和实用性。