基于SVM的密炼机混炼胶的粘度预测

为了提高密炼机混炼胶粘度预测模型的可用性和精确度，在单台机模型的基础上用支持向量机(SVM)非线性回归算法建立了一种新的基于SVM的混炼胶粘度预测模型，并采用此模型对实测数据进行了预测．结果表明，文中所建立的新模型不仅降低了建立预测模型时的工作量，而且提高了预测精度与速度．与多元回归的预测结果相比，新模型具有更好的准确性，可有效用于混炼胶质量指标的在线预测．

Prediction of the Viscosity of Mixed Rubber in Mixer Based on SVM

In order to improve the usability and precision of the model for predicting the viscosity of mixed rubber in mixer, a new predicting model using the nonlinear regression algorithm of Support Vector Machine (SVM) was proposed based on a single-mixer model and the prediction of the measured data was then carried out by the proposed model. The results show that the new model not only simplifies the establishing process of the predicting model but also improves the precision and speed of prediction. It is also shown that, compared with the results obtained by multi-regression, the new model is more accurate and effective when applied to predict the on-line quality indexes of the mixed rubber.