为解决纸张抗张强度预测模型实际相关性差、预测精度低的问题，基于某瓦楞纸厂生产线，通过机理分析筛选出影响抗张强度的生产变量，分别使用偏最小二乘法( PLS)和支持向量机法( SVM) 对抗张强度建模，并通过相关性筛选后的简化模型对模型预测精度进行比较． 结果表明，简化后的支持向量机模型更适合纸张抗张强度的现场预测，其均方根误差为321 N/m，皮尔逊相关系数为0.909，预测速度快且模型精度较高．

In order to solve the problems of poor practicality and low accuracy of the existing paper tensile strengthprediction models,two prediction models respectively based on the partial least-squares ( PLS) and the supportvector machine ( SVM) are established for a corrugated paper mill by selecting parameters affecting paper tensilestrength through mechanism analysis.Then,the two models are simplified by deleting parameters of low correlationwith tensile strength,and the simplified models are compared in terms of prediction accuracy.The results show thatthe simplified SVM model,whose root mean square error and Pearson correlation coefficient are 321N/m and 0.909respectively,is a quick prediction model with a high accuracy,so it is more suitable for the on-line prediction oftensile strength.