Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/27358
Title: Performance of SVM based on PUK kernel in comparison to SVM based on RBF kernel in prediction of yarn tenacity
Authors: Abakar, Khalid AA
Yu, Chongwen
Keywords: Artificial neural network;Pearson VII kernel function (PUK) kernel;Radial basis function kernel;Support vector machines;Yarn properties
Issue Date: Mar-2014
Publisher: NISCAIR-CSIR, India
Abstract: 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.
Page(s): 55-59
ISSN: 0975-1025 (Online); 0971-0426 (Print)
Appears in Collections:IJFTR Vol.39(1) [March 2014]

Files in This Item:
File Description SizeFormat 
IJFTR 39(1) 55-59.pdf78.94 kBAdobe PDFView/Open


Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.