改进决策树算法在企业资源计划系统中的应用  

Improved Decision Tree Algorithms and Its Application in Enterprise Resource Planning

作　　者：李现实[1] 钟秋海[1] 

机构地区：[1]北京理工大学信息科学技术学院自动控制系,北京100081

出　　处：《北京理工大学学报》2006年第2期139-142,共4页Transactions of Beijing Institute of Technology

基　　金：国家自然科学基金资助项目(60274046)

摘　　要：为改进企业资源计划(ERP)的数据挖掘技术和提高利用效率,改善ERP系统的预测功能和决策支持,通过运用改进的混合决策树算法ID3,对企业ERP系统中某些决策判定的依据进行学习,根据学习结果对ERP系统中的新问题进行预测.给出了相关的算法流程和实现步骤.实验结果验证了改进决策树算法在决策预测支持中的有效性和可行性.To improve on the data mining and utilize the efficiency of enterprise resource planning （ERP）, and enhance the function of prediction and decision support of ERP systems, a method is proposed to learn some decision action in ERP systems through the improved decision tree algorithm. Based on the learned result, some prediction support for the new decisions can be obtained in ERP systems. The corresponding approach of algorithms is demonstrated, the test results verify that the improved decision tree algorithm is effective and feasible in predicting decision suooorts.

关 键 词：决策树算法 ID3 企业资源计划(ERP) 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]