多粒化模糊软粗糙集模型

为了扩大粗糙集理论的应用，特别是在模糊环境中的应用，基于模糊软集和模糊蕴涵算子，主要研究基于软模糊近似空间的乐观多粒化模糊软粗糙集模型。该模型将参数集根据客户的不同要求或目标进行重组，只选择若干相关参数集参与计算上、下近似，这样定义的上、下近似不再由整个属性集决定，而是根据重组后的多个属性集一并生成，从而使结果更加符合实际需求。另外，还定义了乐观多粒化模糊软粗糙集模型的截集并讨论了其相关性质。最后给出了算例。

Multi-granulation fuzzy soft rough set model

To enlarge the usage scope of classical rough set theory, particularly in the application of the fuzzy environment, this paper defines the optimistic multi-granulation fuzzy soft rough set model based on fuzzy soft sets and fuzzy implication operator, where a pair of lower and upper optimistic multi-granulation approximations of a fuzzy set are proposed. In fact, this model is constructed based on the recombination of parameter set according to the customers’ particular requirements for parameters. Thus, only parts of parameters are selected to compute the lower and upper optimistic multi-granulation approximations. In addition, it introduces the cut of optimistic multi-granulation rough set and investigates some properties of it. Finally, an example is given to illustrate this model.