摘要
本文目的是探讨精度与程度的复合,探索新的粗糙集拓展模型。从精度与程度的逻辑或运算出发,定义了精度与程度的逻辑或粗糙集模型。在该模型中,通过变精度近似与程度近似的转化公式,研究了精度与程度的逻辑或近似算子,并得到了该近似算子的幂作用等性质。用精度与程度的逻辑或粗糙集模型统一了变精度粗糙集模型、程度粗糙集模型和经典粗糙集模型,并在这些粗糙集模型中得到了近似算子幂作用的相应性质。
This paper is to research combination between precision and grade, and explore new extended rough set models. Based on logical OR operation of precision and grade, rough set model of logical OR operation of precision and grade is defined. In the new model, by conversion formulas between variable precision approximations and graded approximations, approximation operators of logical OR operation of precision and grade are studied, and properties of power action of the approximation operators are achieved. The new model has extended variable precision rough set model, graded rough set model and classical rough set model, and similar properties of power action of approximation operators are achieved in these rough set models.
出处
《模糊系统与数学》
CSCD
北大核心
2010年第3期133-137,共5页
Fuzzy Systems and Mathematics
基金
国家自然科学基金资助项目(10671030)
国家自然科学基金青年科学基金资助项目(60803028)
四川师范大学科学研究基金资助项目(08KYL06)
四川省科技支撑计划项目(09ZC1838)
关键词
人工智能
粗糙集模型
精度
变精度粗糙集
程度
程度粗糙集
逻辑或
Artificial Intelligence
Rough Set Model
Precision
Variable Precision Rough Set
Grade Graded Rough Set
Logical OR Operation
