%A ZHANG Xiao-yan, SANG Bin-bin and WEI Ling %T Fuzzy Entropy and Uncertain Measurement in Lattice-valued Information Systems %0 Journal Article %D 2017 %J Computer Science %R 10.11896/j.issn.1002-137X.2017.09.018 %P 88-92 %V 44 %N 9 %U {https://www.jsjkx.com/CN/abstract/article_558.shtml} %8 2018-11-13 %X In the Lattice-valued information system,the concept of knowledge rough entropy,rough set rough entropy and uncertaint measurement is introduced,and the important properties are obtained.In this paper,it is proved that the knowledge rough entropy increases monotonically when the particle of the knowledge increases and the classification of the information system becomes rough.Further,by discussing the relation between them,the rough entropy of rough sets can be more accurate to measure the degree of rough sets.These conclusions lay a theoretical foundation for the knowledge discovery of Lattice valued information systems.