DocumentCode
1882392
Title
Prediction for Process Capability Index Based on Bayesian Framework LS-SVM
Author
Wu, Shaoxiong
Author_Institution
Dept. of Econ. & Manage., Fujian Univ. of Technol., Fuzhou, China
fYear
2010
fDate
10-12 Dec. 2010
Firstpage
1
Lastpage
4
Abstract
A method of forecasting process capability index was recommended based on least squares support vector machines (LS-SVM). The parameters of LS-SVM were optimized by Bayesian framework. The higher precision model of prediction for process capability index was built by optimizing parameters. The prediction results show it have many advantage, such as lower error and higher fitting, and it can be used to prediction for process capability index.
Keywords
Bayes methods; forecasting theory; least squares approximations; manufacturing industries; process capability analysis; support vector machines; Bayesian framework LS-SVM; forecasting; least squares support vector machines; process capability index; Artificial neural networks; Bayesian methods; Computational modeling; Indexes; Kernel; Predictive models; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5391-7
Electronic_ISBN
978-1-4244-5392-4
Type
conf
DOI
10.1109/CISE.2010.5677266
Filename
5677266
Link To Document