融合云概念的粗糙Vague集的三支决策模型

Vague集是模糊集的扩展模型，从正反两方面来描述事物的不确定性，粗糙Vague集比粗糙模糊集更具有普遍性。目前，三支决策的阈值主要是由单个专家给出，不能反映认知过程中复杂的不确定性形式。针对这一问题，提出了一种融合云概念的粗糙Vague集的三支决策模型。使用基于密度中心的云概念群决策方法求解损失函数，不仅保证综合评价的精度，还为损失函数提供了新的语义解释。构建了粗糙Vague集的三支决策模型并揭示了其误分类代价随着粒度细化而单调递减的规律。通过实验验证了该方法的可行性，克服了现有模糊集在三支决策中对事物不确定性表达不够清楚的缺点。

Three-way decisions model incorporating cloud concept for rough Vague set

Vague set is an extended model of fuzzy set. It describes the uncertainty from both positive and negative aspects. Rough vague set is more general than rough fuzzy set. At present, thresholds for three-way decisions (3WD) are mainly given through a single expert, which fails to reflect the complex forms of uncertainty in cognitive process. To address this problem, this paper proposes a 3WD model for rough vague set merging cloud concept. First, the cloud concept group decision method based on density center is used to solve the loss function, which not only ensures the accuracy of comprehensive evaluation, but also provides a new semantic interpretation for the loss function. Second, the 3WD model for rough vague set is constructed and its misclassification cost decreases monotonically with granularity refinement. Finally, the feasibility of the method is experimentally verified to overcome the drawback that the existing fuzzy sets are mot clear enough to express the uncertainty of things in 3WD model.