Machine learning-based dynamic modeling for process engineering applications: a guideline for simulation and prediction from perceptron to deep learning

HIGHLIGHTS

• who: Carine M. Rebello et al. from the Laboratory of Separation and Reaction, Associate Laboratory LSRE/LCM, Department of, Faculty of, University of Porto, Rua DrRoberto Frias, Porto have published the paper: Machine Learning-Based Dynamic Modeling for Process Engineering Applications: A Guideline for Simulation and Prediction from Perceptron to Deep Learning, in the Journal: Processes 2022, 10, x FOR PEER REVIEW of /2022/
• what: In this scenario this work proposes a guideline for identifying ML models for the different applications in process systems which are usually for simulation or prediction purposes. To perform predictions . . .
  

   

  

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