摘要
为探索预测和控制卷烟焦油量的方法,根据卷烟焦油量与烟叶内在化学成分之间的关系,提出了基于支持向量机的卷烟焦油量预测方法。介绍了支持向量回归估计的学习算法,应用SVM方法建立了基于支持向量机的卷烟焦油量预测模型。计算实例表明,该方法能够根据烟叶中的化学成分测量值来预测卷烟的焦油量。
In order to find out a method for prediction and control of cigarette tar delivery from the relationship between tar delivery and chemical components in tobacco leaf, a prediction method was proposed based on support vector machine （SVM）. The algorithm of support vector for regression estimation was introduced, and the prediction model for tar delivery was established with SVM. The practical examples of calculation indicated that the cigarette tar delivery could be predicted with this method from the chemical components in tobacco leaf.
出处
《烟草科技》
EI
CAS
北大核心
2007年第10期5-8,共4页
Tobacco Science & Technology
关键词
卷烟
焦油
预测模型
化学成分
支持向量机
Cigarette
Tar
Prediction model
Chemical component
Support vector machine
