An evidence combination rule based on a new weight assignment scheme

In evidence theory, conflicting and fuzzy have a significant impact on the results of combination. Nevertheless, existing weight assignment methods can hardly reflect influence combination results. this paper, we address issue by proposing new method for assigning weights corresponding rule. The proposed strengthens consideration evidence. We further incorporate Wasserstein distance to compute clarity degree This is an important reference index in rule effectively reduces ambiguous Using experiments, illustrate justifies its integration process. with also examined set numerical arithmetic Iris datasets. Our confirm that compared four methods, improves decision accuracy, F1 score, computational convergence achieves more reliable fusion