一类支持向量机在烟叶选择中的应用

Application of one-class support vector machine in tobacco leaves selection

为解决卷烟叶组配方中的烟叶替换问题,提出了基于一类支持向量机的烟叶选择方法。介绍了烟叶选择支持向量机建模的原理,分析了影响模型准确性的主要因素,提出了特征选择与支持向量机参数的联合优化策略。应用实例表明,该方法能够根据烟叶中化学成分的测量值来确定烟叶的相似性,为实现烟叶的智能化选择打下了基础。

In order to solve the problem on substitute of tobacco leaves in cigarette blend, a model for selecting tobacco leaves based on one-class support vector machine was proposed. The principle of the model was introduced, and the primary factors influencing the veracity of the model were discussed, then an optimization strategy for the model was presented by joint optimizing of feature selection and parameters for support vector machine. A case study demonstrates that the model could identify the comparability of tobacco leaves according to the measured data of the chemical components of tobacco leaves, which makes it possible to carry out intelligent selection for tobacco leaves.