Recognition of control chart patterns using fuzzy SVM with a hybrid kernel function
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DOI: 10.1007/s10845-015-1089-6
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References listed on IDEAS
- Du, Shichang & Lv, Jun, 2013. "Minimal Euclidean distance chart based on support vector regression for monitoring mean shifts of auto-correlated processes," International Journal of Production Economics, Elsevier, vol. 141(1), pages 377-387.
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Cited by:
- 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.
- Pamela Chiñas-Sanchez & Ismael Lopez-Juarez & Jose Antonio Vazquez-Lopez & Jose Luis Navarro-Gonzalez & Aidee Hernandez-Lopez, 2021. "Out-of-Control Multivariate Patterns Recognition Using D 2 and SVM: A Study Case for GMAW," Mathematics, MDPI, vol. 9(5), pages 1-14, February.
- 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; Fuzzy support vector machine (SVM); Hybrid kernel function; Genetic algorithm;All these keywords.
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