小样本条件下基于属性权重Shapley值分配的粗糙集决策模型

Rough set decision-making model based on shapley value assignment of attribute weight under the condition of small sample

小样本条件下,根据粗糙集理论构建的决策规则受数据来源偶然性误差影响较大,个别数据样本难以反映真实知识关系.为解决小样本条件下粗糙集决策规则可信度未知的问题,提出信息区分量、属性影响方向等概念,运用Shapley值法进行属性权重分配,求取每个属性对决策结果的影响方向,进而得出决策规则的参考信度,以寻求真实可信且适合工程实际的决策规则.实例分析论证了所提方法的可行性以及对数据来源误差的分辨能力.

The decision rules based on the rough set theory under the condition of small samples are greatly affected by the chance error of the initial data, and individual data samples are difficult to reflect the true knowledge relationship.To solve the problem of unknown reliability of rough set decision rules under the condition of small samples, concepts such as the amount of information distinction and the influence direction of attributes are proposed, and attribute weights are assigned using the Shapley value method. The influence direction of each attribute on the decision result is obtained,and the reference reliability of the decision rule is obtained to seek credible and suitable decision-making rules for engineering. Finally, the feasibility of the proposed method and the ability of discriminating the error of the data source are demonstrated through cases.