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Deep evolutionary modeling of condition monitoring data in marine propulsion systems.

, , , and . Soft Comput., 23 (20): 9937-9953 (2019)

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Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0., , , and . Inf. Fusion, (2019)Data-driven prognostics using a combination of constrained K-means clustering, fuzzy modeling and LOF-based score., , , and . Neurocomputing, (2017)Evolutionary LSTM-FCN networks for pattern classification in industrial processes., , , , , and . Swarm Evol. Comput., (2020)Deep evolutionary modeling of condition monitoring data in marine propulsion systems., , , and . Soft Comput., 23 (20): 9937-9953 (2019)Adaptive Dendritic Cell-Deep Learning Approach for Industrial Prognosis Under Changing Conditions., , , , , , and . IEEE Trans. Ind. Informatics, 17 (11): 7760-7770 (2021)Quantile regression forests-based modeling and environmental indicators for decision support in broiler farming., , , , and . Comput. Electron. Agric., (2019)Data Augmentation for Industrial Prognosis Using Generative Adversarial Networks., , , and . IDEAL (2), volume 12490 of Lecture Notes in Computer Science, page 113-122. Springer, (2020)Kernel Density-Based Pattern Classification in Blind Fasteners Installation., , , , , and . HAIS, volume 10334 of Lecture Notes in Computer Science, page 195-206. Springer, (2017)