Integration of support vector machines and control charts for multivariate process monitoring

DOI10.1080/00949651003789074zbMath1431.62682OpenAlexW2030118725MaRDI QIDQ4914964

Panitarn Chongfuangprinya, Seoung Bum Kim, Thuntee Sukchotrat, Sun-Kyoung Park

Publication date: 16 April 2013

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949651003789074

zbMATH Keywords

bootstrapdata miningsupport vector machinesmultivariate control chartsstatistical quality control

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

A hybrid ICA-SVM approach for determining the quality variables at fault in a multivariate process

Cites Work

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• Tuned artificial contrasts to detect signals
• Kernel distance-based robust support vector methods and its application in developing a robust K-chart

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