摘要
粗糙集方法能客观、有效地对有限指标数据进行挖掘,通过属性约简剔除冗余指标,并根据属性重要度生成指标权重,系统地探讨了利用粗糙集进行指标体系优化和综合评价的全过程思路及方法,并通过同行评议专家科技信用评价实例,验证了方法的实用性.
Rough set can be used in data mining from finite indicator data,both objectively and efficiently,eliminate redundant indicators through attribute reduction and generate indicator weights through attribute significance.The whole process and method of applying rough set into indicator system optimization and comprehensive evaluation are systematically probed into,and testifies by scientific and technological credit evaluation of peer evaluation experts.
出处
《浙江大学学报（理学版）》
CAS
CSCD
北大核心
2010年第4期411-415,共5页
Journal of Zhejiang University（Science Edition）
基金
交通部重点软科学项目(20071g0004)
关键词
粗糙集
指标体系
综合评价
属性约简
属性重要度
rough set
indicator system
comprehensive evaluation
attribute reduction
attribute significance
