面向Apriori算法的数据挖掘技术在仓储配置优化中的应用  

Application of the Data Mining Technology oriented the Apriori Algorithm in Optimization of Storage Configuration

作　　者：陈先宇[1] 

机构地区：[1]重庆交通大学,重庆南岸400074

出　　处：《通化师范学院学报》2015年第6期9-11,48,共4页Journal of Tonghua Normal University

摘　　要：该文采取关联规则及Apriori算法从历史交易数据中获取库存商品的关联关系,给出一种置信度转化为商品之间购买距离的方法,在此基础上利用K-中心点聚类算法,将商品按照库存的种类和购买距离进行聚类,从而得到仓储配置优化方案,文中给出了相关概念和算法,并举例验证了所提出方法的有效性.The incidence relation of commodities in the stocks is computed by the asocciation rules and the Apriori algorithm based on the historical trading data in this paper. A method to convert the confidence coeffi- cient into the by distance of commodities is proposed. By using the K - means clustering algorithm, the commodities are clustered as different categories and the optimized storage configuration is obtained. The related concepts and algorithms are presented. An example of storage configuration is also given to show the feasibility of the proposed method in this study.

关 键 词：数据挖掘 APRIORI算法 仓储 优化 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]