多源覆盖信息系统下的加权广义多粒度粗糙集模型及其应用

考虑到多源覆盖信息系统中数据的复杂性以及单个信息系统之间的不平等性，引入诱导覆盖粗糙集，并对信息系统的属性赋予权重值，提出了多源覆盖信息系统下的加权广义多粒度粗糙集MCS-WGMRS模型。定义了属性权重的计算方法，给出模型的上、下近似，并获取了相应的决策规则。通过实例分析验证了MCS-WGMRS模型的有效性，结果表明该模型对目标集的分类能力更强，适当调整阈值可进一步提高模型的容错性。

A weighted generalized multi-granulation rough set model of multi-source covering information system and its applications

Considering the complexity of data in multi-source covering information systems and the inequality between individual information systems, this paper introduces the induced covering rough set and assigns weight values to each single information system’s attribute, and, consequently, proposes a weighted generalized multi-granulation rough set of multi-source covering information systems. Firstly, it defines the calculation method of attribute’s weight. Then, it gives complete upper and lower approximations of the model, and acquires the corresponding decision rule. Finally, it verifies the validity of the model through an example analysis. The experimental results show that the model has a better ability to classify the target set, and its fault tolerance can be further improved with appropriate adjustment of the threshold.