Performance of SVM based on PUK kernel in comparison to SVM based on RBF kernel in prediction of yarn tenacity

被引:1
|
作者
Abakar, Khalid A. A. [1 ]
Yu, Chongwen [1 ]
机构
[1] Donghua Univ, Coll Text, Shanghai 201620, Peoples R China
关键词
Artificial neural network; Pearson VII kernel function (PUK) kernel; Radial basis function kernel; Support vector machines; Yarn properties; SUPPORT VECTOR REGRESSION; ARTIFICIAL NEURAL-NETWORK; MACHINES;
D O I
暂无
中图分类号
TB3 [工程材料学]; TS1 [纺织工业、染整工业];
学科分类号
0805 ; 080502 ; 0821 ;
摘要
A new kernel function of SVM based on the Pearson VII function has been applied and compared with the commonly applied kernel functions, i.e. the polynomial and radial basis function (RBF), to predict yarn tenacity. It is found that the SVM model based on Pearson VII kernel function (PUK) shows the same applicability, suitability, performance in prediction of yarn tenacity as against SVM based RBF kernel. The comparison with the ANN model shows that the two SVM models give a similar predictive performance than ANN model.
引用
收藏
页码:55 / 59
页数:5
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