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由于客观世界的复杂性与不确定性以及人类认知的有限性,现实的决策信息系统总是包括大量的偏好信息、灰色信息、噪声数据,而基于传统粗造集方法难以有效处理。鉴于此,本文利用灰色系统的思想与方法,构建了一种基于优势灰度的变精度粗糙集模型。该方法,利用灰数和灰度的最新研究成果,提出优势灰度的概念,以其确定对象间的优势关系,并将基于优势灰度的优势关系代替变精度粗糙集的不可分辨关系,构建了优势变精度粗糙集模型,最后以实例验证了模型的有效性与适用性。结果表明,通过调整阀值参数,模型具有一定的容错能力,能够有效地提取决策规则,进行科学决策。
Due to the complexity and uncertainty of the objective world and the limited human cognition, the reality of decision-making information system always includes a large amount of preference information, gray information and noise data, but it is difficult to process effectively based on the traditional rough set method. In view of this, this paper constructs a variable precision rough set model based on the dominant gray using the ideas and methods of gray system. This method uses the latest research achievements of gray numbers and grayscale to propose the concept of dominant grayscale to determine the dominant relationship between objects and substitute the dominant relations based on dominant grays for the indivisible relations of variable precision rough sets The advantage variable precision rough set model is given, and finally the validity and applicability of the model are verified by examples. The results show that by adjusting the threshold parameters, the model has a certain degree of fault tolerance, which can effectively extract decision rules and make scientific decisions.