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Deep causal mining for plant-wide oscillations with multilevel Granger causality analysis.

, , , and . ACC, page 5056-5061. IEEE, (2016)

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Deep causal mining for plant-wide oscillations with multilevel Granger causality analysis., , , and . ACC, page 5056-5061. IEEE, (2016)Model-Predictive Control in Practice., and . Encyclopedia of Systems and Control, Springer, (2015)Quality Relevant Data-Driven Modeling and Monitoring of Multivariate Dynamic Processes: The Dynamic T-PLS Approach., , , and . IEEE Trans. Neural Networks, 22 (12): 2262-2271 (2011)Feature selection based on concurrent projection to latent structures for high dimensional spectra data., , , , and . ICIA, page 234-239. IEEE, (2016)Attention-mechanism based DiPLS-LSTM and its application in industrial process time series big data prediction., , and . Comput. Chem. Eng., (August 2023)Distributed optimization of multi-building energy systems with spatially and temporally coupled constraints., , , and . ACC, page 2913-2918. IEEE, (2017)Multi-directional reconstruction based contributions for root-cause diagnosis of dynamic processes., , and . ACC, page 3500-3505. IEEE, (2014)Experimental study of economic model predictive control in building energy systems., , and . ACC, page 3753-3758. IEEE, (2013)Dynamic Processes Modeling and Monitoring based on a Novel Dynamic Latent Variable Model., , , and . CAA SAFEPROCESS, page 589-595. IEEE, (2019)Progressive Parametrization in Subspace Identification Models with finite horizons., , , and . CDC, page 2819-2824. IEEE, (2010)