Abstract: Fabric’s shearing property has a close relation with the factors such as fiber，yarn and fabric structures.In order to design the fabric’s shearing property scientifically，a new method is proposed to predict the fabric’s shearing property with support vector machine.The nonlinear relationship between fabric structural parameter and fabric’s shearing property is presented，and the relative model is built.After normalized，the sampling data are inputted into the model.Then cross-validation is used to select the optimal parameters and the obtained optimal parameters are used to predict the fabric’s shearing property.Compared with BP Artificial Neural Network（ANN） method，the predicted results show the presented method is more accuracy.

摘要： 织物的剪切性能受到纱线和多种织物结构参数的影响，为了科学地设计织物剪切性能，提出了织物剪切性能预测的一种新方法－支持向量机，用它来表达织物剪切性能与织物结构参数之间复杂的非线性关系，并建立了相应的预测模型。对获得的样本进行归一化处理后，将其输入预测模型，然后采用交叉验证的方法获得模型的最佳参数，利用获得的最佳参数来进行剪切性能的预测。将获得的结果同BP神经网络预测的结果进行了比较，结果表明该方法的预测精度较高。