Using fuzzy aggregation theory and rough set theory, this article puts out a weight allocation method based on impersonal message entropy.
借助模糊聚类技术和粗糙集理论提出了一个基于客观信息熵的多因素权重分配方法。
The rough entropy of the uncertainty of ordinary set and fuzzy set, and the monotonous relation between the uncertainty of these two kinds of set and their corresponding rough entropy, are discussed.
并研究了与普通集合和模糊集合的不确定性相对应的粗糙信息熵，以及这两种集合的不确定性与其对应的粗糙信息熵之间的单调关系。
Rougness, rough entropy, fuzziness, and fuzzy entropy are major methods for measuring the uncertainty of rough sets.
粗糙集的不确定性度量方法，目前主要包括粗糙集的粗糙度、粗糙熵、模糊度和模糊熵。
Moreover, the modified rough entropy and the fuzzy entropy based on equivalence relation is extended to the generalized modified rough entropy and the generalized fuzzy entropy.
并分别将基于不可分辨关系下的修正粗糙熵和模糊熵拓展到基于一般二元关系下的广义修正粗糙熵和广义模糊熵。
A method with the fuzzy entropy for measuring fuzziness to fuzzy problem in rough sets is proposed.
针对粗糙集中存在的模糊性问题，提出了一种利用模糊熵测量其模糊性的方法。
Then the membership matrix obtained by clustering algorithm was used to reduce attribute set. Finally, based on entropy, a knowledge acquisition method of fuzzy Rough Set (RS) was put forward.
进而将聚类得到的属性隶属矩阵用于属性约简，并提出一种基于信息熵的模糊粗糙集知识获取的方法。
Then the membership matrix obtained by clustering algorithm was used to reduce attribute set. Finally, based on entropy, a knowledge acquisition method of fuzzy Rough Set (RS) was put forward.
进而将聚类得到的属性隶属矩阵用于属性约简，并提出一种基于信息熵的模糊粗糙集知识获取的方法。
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