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Disambiguation of "Yan, Shifu"

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Data-Driven Soft Sensing for Batch Processes Using Neural Network-Based Deep Quality-Relevant Representation Learning.

, , , and . IEEE Trans. Artif. Intell., 4 (4): 602-611 (2023)

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To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Yan Yan

Shanshan Yan

Americanization in China: an analysis of General Motors and its strategies in China. Uni Mainz, (2009)

Yan Xu

Untersuchungen zur Verleimung von Holz und Holzspanplatten mit UF-Leimharzen und PMDI. TU Braunschweig, (2009)

Yan Zhang

Yan Xu

 

Other publications of authors with the same name

Design teacher and supervised dual stacked auto-encoders for quality-relevant fault detection in industrial process., and . Appl. Soft Comput., (2019)Local-Global Modeling and Distributed Computing Framework for Nonlinear Plant-Wide Process Monitoring With Industrial Big Data., , , and . IEEE Trans. Neural Networks Learn. Syst., 32 (8): 3355-3365 (2021)Data-Driven Two-Dimensional Deep Correlated Representation Learning for Nonlinear Batch Process Monitoring., , , , and . IEEE Trans. Ind. Informatics, 16 (4): 2839-2848 (2020)Nonlinear quality-relevant process monitoring based on maximizing correlation neural network., and . Neural Comput. Appl., 33 (16): 10129-10139 (2021)CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis., , , , , , , and . KDD, page 4310-4320. ACM, (2022)Learning Output Relevant Features by Joint Autoencoder., and . IEEE Trans. Cybern., 54 (2): 1075-1083 (February 2024)Neural representations for quality-related kernel learning and fault detection., , and . Soft Comput., 27 (18): 13543-13551 (2023)Data-Driven Soft Sensing for Batch Processes Using Neural Network-Based Deep Quality-Relevant Representation Learning., , , and . IEEE Trans. Artif. Intell., 4 (4): 602-611 (2023)Fluid catalytic cracking process quality-driven fault detection based on partial least squares and deep feedforward neural network., , , , , and . Trans. Inst. Meas. Control, 46 (1): 78-92 (January 2024)