双论域程度多粒度粗糙模糊集模型  

Dual Domain Graded Multi-granulation Rough Fuzzy Set Model

作　　者：王菊 傅丽[1] WANG Ju;FU Li(College of Mathematics and Statistics,Qinghai Minzu University,Xining 810000,Qinghai)

机构地区：[1]青海民族大学数学与统计学院,青海西宁810000

出　　处：《商洛学院学报》2025年第2期16-23,51,共9页Journal of Shangluo University

基　　金：青海民族大学研究生创新项目(07M2023007)。

摘　　要：提出了一种融合程度粗糙集与多粒度粗糙集的新型模型---双论域程度多粒度粗糙模糊集,该模型允许在概念近似逼近过程中接受有限的分类误差,提升了模型的容错能力。在模型构建方面,将已有的单论域模型扩展至双论域,定义了双论域程度多粒度粗糙模糊集模型的上近似算子和下近似算子,同时探讨了这些算子的性质。通过具体案例分析,验证了所提出模型的性质,并展示了通过调整参数k,可以优化分类结果。A new model,the dual domain degree multi granularity rough fuzzy set,which integrates degree rough sets and multi granularity rough sets,is proposed.This model allows for limited classification errors in the conceptual approximation process,improving the model's fault tolerance.In terms of model construction,the existing single domain model was extended to a dual domain model,and the upper and lower approximation operators of the dual domain degree-multi granularity rough fuzzy set model were defined,while exploring the properties of these operators.Through specific case analysis,the properties of the proposed model were verified,and it was demonstrated that by adjusting the parameter k,the classification results can be optimized.

关 键 词：模糊集 双论域 程度粗糙集 多粒度粗糙集 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]