Recognition of abnormal patterns in industrial processes with variable window size via convolutional neural networks and AdaBoost
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DOI: 10.1007/s10845-021-01907-8
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- Ling-Jing Kao & Tian-Shyug Lee & Chi-Jie Lu, 2016. "A multi-stage control chart pattern recognition scheme based on independent component analysis and support vector machine," Journal of Intelligent Manufacturing, Springer, vol. 27(3), pages 653-664, June.
- Xueliang Zhou & Pingyu Jiang & Xianxiang Wang, 2018. "Recognition of control chart patterns using fuzzy SVM with a hybrid kernel function," Journal of Intelligent Manufacturing, Springer, vol. 29(1), pages 51-67, January.
- Min Zhang & Wenming Cheng, 2015. "Recognition of Mixture Control Chart Pattern Using Multiclass Support Vector Machine and Genetic Algorithm Based on Statistical and Shape Features," Mathematical Problems in Engineering, Hindawi, vol. 2015, 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.
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Keywords
CCPR; Mixed CCP; CNN; Deep learning; Bayesian optimization; Control chart pattern recognition;All these keywords.
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