Development of a Robust Data-Driven Soft Sensor for Multivariate Industrial Processes with Non-Gaussian Noise and Outliers
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- Chien-Chih Wang & Hsin-Tzu Chang & Chun-Hua Chien, 2022. "Hybrid LSTM-ARMA Demand-Forecasting Model Based on Error Compensation for Integrated Circuit Tray Manufacturing," Mathematics, MDPI, vol. 10(13), pages 1-16, June.
- Hongxun Wang & Lin Sui & Mengyan Zhang & Fangfang Zhang & Fengying Ma & Kai Sun, 2021. "A Novel Input Variable Selection and Structure Optimization Algorithm for Multilayer Perceptron-Based Soft Sensors," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-10, May.
- Gijbels, I. & Vrinssen, I., 2015. "Robust nonnegative garrote variable selection in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 85(C), pages 1-22.
- Wang, Hansheng & Li, Guodong & Jiang, Guohua, 2007. "Robust Regression Shrinkage and Consistent Variable Selection Through the LAD-Lasso," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 347-355, July.
- Song, Xiao & Han, Daolin & Sun, Jinghan & Zhang, Zenghui, 2018. "A data-driven neural network approach to simulate pedestrian movement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 827-844.
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Keywords
date-driven modelling; soft sensor; multilayer perceptron; LASSO; maximal information coefficient; robust estimation;All these keywords.
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