摘要
经典决策粗糙集模型仅仅依据单个代价矩阵进行风险决策,没有考虑到风险代价的多样性和复杂性。为了弥补现有模型的不足,首先,从加权投票机制的角度引入基于多重代价融合的风险分析方法,提出一种基于加权代价的决策粗糙集方法。然后,研究基于加权代价的决策粗糙集模型与其他模型的性质和关系,分析它们之间的度量和代价关系。最后,通过UCI数据集验证该方法的有效性和鲁棒性。
Classical decision-theoretic rough set was proposed based on only one cost matrix,which dose not take the diversity and complexity of cost into account.To make up for the shortcomings,a risk analysis method based on multi-cost fusion was introduced and a decision-theoretic rough set method based on weighted multi-cost was proposed.Futher-more,the properties and the relations of these kinds of rough sets were discussed.The measure and cost relations of them were analyzed.Finally,the validity and robustness of the method were verified by UCI dataset.
作者
陈玉金
李续武
CHEN Yu-jin;LI Xu-wu(College of Air and Missile Defense,Air-force Engineering University,Xi'an 710051,China)
出处
《计算机科学》
CSCD
北大核心
2017年第12期239-244,共6页
Computer Science
基金
国家自然科学基金(61503407)资助
关键词
决策粗糙集
多重代价
权重
度量
Decision-theoretic rough set
Multi-cost
Weight
Measurement