Title: Prediction Method for Machining Quality Based on Weighted Least Squares Support Vector Machine
Abstract: A new machining error prediction approach, which is based on the weighted least squares support vector machine (LS-SVM), was given. The nearer sample was set a larger weight, while the farther was set the smaller weight in the history data. In the same condition, the results show that the prediction accuracy of the weighted LS-SVM is 40% higher than that of the standard LS-SVM. Compared with other more modeling approaches, the prediction effect indicates that the proposed method is more accurate and can be realized more easily. It provides a better way for on-line quality monitoring and controlling of dynamic machining
Publication Year: 2006
Publication Date: 2006-01-01
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 6
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