A multi-stage control chart pattern recognition scheme based on independent component analysis and support vector machine
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DOI: 10.1007/s10845-014-0903-x
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References listed on IDEAS
- Chih-Hsuan Wang & Way Kuo & Hairong Qi, 2007. "An integrated approach for process monitoring using wavelet analysis and competitive neural network," International Journal of Production Research, Taylor & Francis Journals, vol. 45(1), pages 227-244, January.
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Cited by:
- Yun Bai & Zhenzhong Sun & Bo Zeng & Jianyu Long & Lin Li & José Valente Oliveira & Chuan Li, 2019. "A comparison of dimension reduction techniques for support vector machine modeling of multi-parameter manufacturing quality prediction," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2245-2256, June.
- Yuehjen E. Shao & Po-Yu Chang & Chi-Jie Lu, 2017. "Applying Two-Stage Neural Network Based Classifiers to the Identification of Mixture Control Chart Patterns for an SPC-EPC Process," Complexity, Hindawi, vol. 2017, pages 1-10, October.
- Tao Zan & Zhihao Liu & Hui Wang & Min Wang & Xiangsheng Gao, 2020. "Control chart pattern recognition using the convolutional neural network," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 703-716, March.
- Ahmed Maged & Min Xie, 2023. "Recognition of abnormal patterns in industrial processes with variable window size via convolutional neural networks and AdaBoost," Journal of Intelligent Manufacturing, Springer, vol. 34(4), pages 1941-1963, April.
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Keywords
Control chart pattern recognition; Signal separation; Independent component analysis; Support vector machine;All these keywords.
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