Abstract: To improve the configuration of intelligent manufacturing resources,a new method of attribute selection was proposed.Based on the attribute characteristics of intelligent manufacturing resource system,a large number of unordered resource attributes were decomposed into redundant attributes and core attributes through the proposed method.The distribution of attribute characteristic variables in the same space was researched with information entropy,and the redundancy among the attribute characteristic variables was researched with mutual information.On this basis,the resource attributes feature selection model was constructed,and the simulation was carried out to validate this model.The results showed that the resource with robust attributes features was searched quickly and accurately from the mass of intelligent manufacturing resources,which could improve the resource allocation efficiency.

Key words: intelligent manufacturing, resource allocation, redundancy, mutual information, feature selection

摘要： 为改善智能制造资源的配置过程,提出一种属性特征选择方法。从智能制造资源系统的属性特征入手,将大量无序的资源属性特征分解为冗余属性资源和核属性资源并进行特征选择;采用信息熵研究了同态空间中属性特征变量的属性值分布规律;采用互信息研究了属性特征变量之间的冗余性。构建了资源属性特征选择模型,并使用样本数据对该模型进行了仿真,结果表明该模型能够在海量的智能制造资源中快速、准确地找出具有鲁棒性属性特征的资源,提高了资源配置效率。

关键词: 智能制造, 资源配置, 冗余性, 互信息, 特征选择