双论域上的广义直觉模糊概率粗糙集模型及其应用

Generalized intuitionistic fuzzy probabilistic rough set models on two universes and their applications

已有的双论域直觉模糊概率粗糙集模型通过设置两个阈值λ_(1)、λ_(2),讨论了经典集合在直觉模糊二元关系下的概率粗糙下上近似。该模型不能计算直觉模糊集合在直觉模糊二元关系下的概率粗糙下上近似,这在一定程度上限制了该模型的应用。首先给出了直觉模糊条件概率的定义。在直觉模糊概率空间下构造了双论域广义直觉模糊概率粗糙集模型,讨论了模型的主要性质。最后,将模型应用到临床诊断系统中。与其他模型相比,所提出的广义直觉模糊概率粗糙集模型进一步丰富了概率粗糙集理论,更适合于实际应用。

In the existing intuitionistic fuzzy(IF)probabilistic rough set model of two universes,the probabilistic rough lower and upper approximations of a classical set under IF binary relation are discussed by setting two thresholds,λ_(1) and λ_(2).However,this model is unable to calculate the probabilistic rough lower and upper approximations of IF sets under IF binary relation,which limits the application of this model to a certain extent.In this study,we first define the IF conditional probability.Then,the generalized IF probability rough set models are constructed in IF probabilistic approximation space.In addition,the main properties of the model are discussed.Finally,the numerical examples of clinical diagnostic systems are applied to illustrate the validity of the proposed models.Compared with other models,the proposed generalized IF probabilistic rough set models further enrich the probabilistic rough set theory and are more suitable for practical applications.