摘要
产量预测对于生产和销售部门是极其重要的。在石化企业中,由于影响主副产品关系的因素很多,产量很难预测。传统的机器学习方法在这个领域的应用存在着一些局限性。论文介绍了一种数据挖掘中的支持向量机方法,较好地解决了产量预测问题,同时也对生产优化有着一定帮助。文中首先介绍数据挖掘及其相关理论,重点阐述了支持向量机方法,接下来详细地介绍了问题求解过程。
The forecast of the byproduct productionm is very important to production and sale department.But in Petrochemical enterprise,it is so difficult to forecast because many factors would affect the relation of main product and byproduct.The traditional Machine Learning Method has some limitation in the application of this field.This paper introduces a kind of DM theory--SVM,by means of which could not only satisfiedly solve this problem,but also help with production optimization.Firstly DM theory is introduced,which emphasize on SVM.After that the process of problem solution is presented in detail.
出处
《计算机工程与应用》
CSCD
北大核心
2004年第30期208-210,共3页
Computer Engineering and Applications
