Advances in Machine Learning Methods for Process Systems Engineering

Chair(s):
Wang, Z., The Dow Chemical Company
Co-chair(s):
Zhang, Q., University of Minnesota

Data-driven approaches are playing an increasingly significant role in chemical engineering. This session solicits submissions pertaining to both methodological advances in machine learning as well as application-driven case studies demonstrating the use data and machine learning to infer correlations, develop models, as well as to improve processes/systems through data-driven optimization and control. Particular emphasis will be given to applications which employ an adaptive data-driven approach, through which data-mining and machine learning are used to create intelligent systems, which adaptively learn from the data.

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Individuals

AIChE Members $150.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
Non-Members $225.00