基于粗糙集和模糊聚类的评价方法研究

A Study on the Assessment Method Based Coarse Sets and Ambiguous Agglomeration

利用模糊聚类的方法实现连续性指标值的离散化,对分析对象进行分类以获取指标的粗糙数,应用粗糙集约简方法生成约简的指标集并确定指标属性的权重以对其进行综合评价。这种新的评价方法将RS和模糊聚类有机地融合起来,可以充分发挥两种方法的各自优势。最后通过上市公司业绩评价实例验证了此方法的实用性。

By application the ambiguous agglomeration method,continuous data can be transformed into discrete ones.And by classification of the objects for analysis,coarse data sets can be obtained.Such a data reduction method results in a reduced indications set,and,by endowing the weights,it can be served as a comprehensive assessment method.The method combines up RS with ambiguous agglomeration and thus take the advantage of both of them.This paper applies the method to the case of a listed corporation,with the empirical analysis turning out the effectiveness of the method.