基于RS和SVM的动态供应链成员选择算法

发布时间：2018-04-19 05:07

本文选题：动态供应链 + 成员选择　；参考：《数学的实践与认识》2014年06期

【摘要】：良好的成员选择方法是动态供应链平稳运行的重要基础,针对动态供应链成员选择时面临决策属性多且可供决策分析数据样本少的难题,提出了基于粗糙集和支持向量机的动态供应链成员选择算法,核心是应用粗糙集进行属性约简,然后结合支持向量机进行链上成员分类.方法在保证不会降低分类性能的前提下,达到降低数据维数和分类过程中复杂度的目的.
[Abstract]:A good member selection method is an important foundation for the smooth operation of the dynamic supply chain. In view of the problem that there are many decision attributes and few data samples for decision analysis in the selection of the members of the dynamic supply chain.A dynamic supply chain member selection algorithm based on rough set and support vector machine is proposed. The core of this algorithm is to use rough set to reduce attributes and then combine support vector machine to classify members on the chain.The method can reduce the data dimension and the complexity of the classification process without reducing the classification performance.
【作者单位】：桂林电子科技大学商学院;北京科技大学东凌经济管理学院;
【基金】：教育部人文社会科学研究青年基金(11YJC630290) 广西高等学校科研资助(200103YB050)
【分类号】：F274;TP18

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