基于LS—SVM的棉／氨纶弹力布热定形效率预测

针对热定形大样实验数据较少的问题，提出以基于最小二乘支持向量机（1east squares support vectormachine，IS—SVM）方法建立棉／氨纶弹力布热定形效率预测模型，该方法基于统计学习理论的原理，能较好地解决小样本、非线性的学习问题。将该方法与传统的多元非线性回归方法进行比较，试验结果表明，该方法具有更高的精度，验证了LS—SVM对热定形效率预测建模是一种可行且有效的方法。

Heat - setting Efficiency Model of Cotton - spandex Knit Goods Based on LS - SVM

Based on least squares support vector machine （LS - SVM）, a heat - setting efficiency model of cotton knitted fabric containing spandex was proposed in accordance with the features of small samples prediction. The model was established by the principle of statistical learning theory, so that problems contain small samples and non - linear study could be easily solved by this method. The presented method was compared with the traditional method of multivariate nonlinear regression. Test results showed that the former had a higher precision and verified the feasibility and effectiveness of the model for heat - setting efficiency.