计算机科学 ›› 2017, Vol. 44 ›› Issue (12): 239-244.doi: 10.11896/j.issn.1002-137X.2017.12.043
陈玉金,李续武
CHEN Yu-jin and LI Xu-wu
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。
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