协调广义多尺度序模糊决策系统的最优尺度组合与属性约简
Optimal Scale Combinations and Attribute Reduction for Consistent Generalized Multi-scale Ordered Fuzzy Decision Systems
朱康 1吴伟志 1刘梦欣1
作者信息
- 1. 浙江海洋大学信息工程学院 舟山 316022
- 折叠
摘要
针对广义多尺度序模糊决策系统的知识获取问题,首先,在广义多尺度序模糊决策系统中定义优势关系,给出广义多尺度序模糊决策系统中信息粒的表示,同时定义在不同尺度组合下集合关于属性子集在优势关系下的下近似与上近似的概念.然后,在协调广义多尺度序模糊决策系统中定义5种最优尺度组合的概念,使用基于证据理论的信任函数与似然函数刻画最优尺度组合的数值特征,证明信任最优尺度组合与下近似最优尺度组合是等价的,似然最优尺度组合与上近似最优尺度组合也是等价的,并在信任最优尺度组合的基础上给出属性约简方法,同时给出最优尺度组合和属性约简的搜索算法.最后,在UCI数据集上的实验验证文中方法和算法的可行性与有效性.
Abstract
Aiming at knowledge acquisition in generalized multi-scale ordered fuzzy decision systems,dominance relations in generalized multi-scale ordered fuzzy decision systems are firstly defined,information granules with different scale combinations in these systems are then constructed.Lower and upper approximations of sets with respect to dominance relations determined by an attribute set under different scale combinations are also defined.Five concepts of optimal scale combinations in consistent generalized multi-scale ordered fuzzy decision systems are defined.The numerical characteristics of these optimal scale combinations are described by belief and plausibility functions in the evidence theory.It is proved that belief optimal scale combinations are equivalent to lower approximate optimal scale combinations,and plausibility optimal scale combinations are equivalent to upper approximate optimal scale combinations.An attribute reduction approach based on a belief optimal scale combination is explored,and optimal scale combinations and attribute reduction search algorithms are formulated.Finally,experiments on UCI datasets verify the feasibility and validity of the proposed method and algorithms.
关键词
证据理论/粒计算/多尺度序信息系统/最优尺度组合/粗糙集Key words
Evidence Theory/Granular Computing/Multi-scale Ordered Information Systems/Opti-mal Scale Combinations/Rough Sets引用本文复制引用
基金项目
国家自然科学基金项目(12371466)
国家自然科学基金项目(62076221)
出版年
2024
NETL
NSTL
万方数据