Machine Learning and Big Data (2)

ON-SITE: Main Hall 21 June 2022, 15:40–17:20 (JST/UTC+9)
ON-LINE:
JST   Chaired by Artur Maria Schweidtmann (Delft University of Technology) and Calvin Tsay (Imperial College London)


15:40
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16:00
  Proceeding #: 259
Using Reinforcement Learning in a Game-like Setup for Automated Process Synthesis Without Prior Process Knowledge
Quirin Göttl, Dominik G. Grimm and Jakob Burger


16:00
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16:20
  Proceeding #: 260
Generation and Benefit of Surrogate Models for Blackbox Chemical Flowsheet Optimization
Tim Janus, Felix Riedl and Sebastian Engell


16:20
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16:40
  Proceeding #: 261
Flowsheet recognition using deep convolutional neural networks
Lukas Schulze Balhorn, Qinghe Gao, Dominik Goldstein and Artur M. Schweidtmann


16:40
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17:00
  Proceeding #: 262
Active learning for multi-objective optimization of processes and energy systems
Julia Granacher and François Maréchal


17:00
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17:20
  Proceeding #: 263
Data-driven Stochastic Optimization of Numerically Infeasible Differential Algebraic Equations: An Application to the Steam Cracking Process
Burcu Beykal, Zahir Aghayev, Onur Onel, Melis Onel and Efstratios N. Pistikopoulos

JST: Japan Standard Time (UTC+9).
Time with asterisk* indicates the time of the date one day before.
Time with double dagger indicates the time of the date one day after.