基于多粒度决策粗糙集的云计算产品分类方法

Cloud Computing Product Classification Method Based on Multi-granularity Decision Rough Set

粗糙集理论中一个重要的研究课题是残缺区间决策系统。针对现有决策系统存在分类精度和质量较低的问题,结合可能性相似度容差关系的优良特性,并运用粗糙集理论,设计出一种新的多粒度决策模型。基于属性的视角,重新定义容差关系,并基于此方法,借鉴多粒度决策粗糙集具有一定容错能力和能够多层次处理数据的优势,结合粗糙集的优良特征,提出一种新的多粒度决策模型,然后着重讨论了多粒度决策粗糙集模型的基本性质和度量参数。最后通过云计算产品分类实例,验证了改进的多粒度决策粗糙集模型可有效提高对象的分类精度和分类质量。

An important research topic in rough set theory is incomplete interval decision-making system.Aiming at the problem of low classification accuracy and quality in the existing decision system,by using rough set theory,a new multi-granularity decision model is designed,which combines the excellent characteristics of possibility similarity tolerance relation.This paper redefines the tolerance relation from the perspective of attributes,and combining with the good features of rough sets,a novel multi-granularity decision model is proposed,referring to the advantages of multi-granularity decision-making rough set,such as fault-tolerance ability and multi-level data processing ability.The basic characteristics and quantity parameter of multi-granularity decision-making rough set model are discussed emphatically.Finally,an example of cloud computing product classification shows that the improved multi-granularity decision-making rough set model can effectively improve the classification accuracy and quality of objects.