摘要
针对综合评价过程中如何处理不确定性信息,进行智能评价等难点问题,基于粗糙集理论进行指标筛选与权重确定,构建基于粗糙集的综合评价模型.首先,利用粗糙集属性约简与重要度原理,有效删除冗余指标,得到最简指标体系,并求得各指标的重要性,从而客观确定权重.其次,进一步将粗糙集理论与模糊集理论和可拓评价分别杂合,拓展将多学科理论与综合评价理论相融合的新思路,建立模糊粗糙与粗糙可拓综合评价模型,研究并实现新模型的智能求解算法.最后,通过一个实例阐明所提出评价方法能更加有效地精简指标体系,提高权重确定的客观性,说明所设计模型及算法是科学合理的.
In this paper, we build a comprehensive evaluation model by using index selection and weight- determining method based on rough set theory to deal with the uncertainty information in intelligent evalu- ation. First, the minimalist index system and importance of each index are obtained by effectively removing redundant indicators based on rough set attribute reduction principle and attribute importance principle. Thus the weights are objectively determined. Second, a fuzzy rough evaluation model and a coarse exten sion synthetic evaluation model are set up respectively by hybridizing rough set theory respectively with fuzzy set theory and the extension evaluation theory. And an intelligent algorithm is developed to solve the two models. Finally, computational experiments show that the proposed evaluation method can effectively reduce the index system and improve the objectivity of weight, which shows the models are scientific and the algorithm is effective.
出处
《湖南工程学院学报（自然科学版）》
2016年第2期44-49,共6页
Journal of Hunan Institute of Engineering(Natural Science Edition)
基金
湖南省哲学社会科学规划基金办公室(13YBB158)
湖南省教育科学"十二五"规划课题(XJK014BZY021)
关键词
粗糙集
综合评价
可拓评价
指标约简
rough set
comprehensive evaluation
extension evaluation theory
indicator reduction
