Data-Driven Process Optimization Considering Surrogate Model Prediction Uncertainty: A Mixture Density Network-Based Approach
Author:
Affiliation:
1. Department of Chemical and Materials Engineering, University of Alberta, 9211 116 Street, Edmonton, Alberta, Canada T6G1H9
2. Department of Chemical Engineering, National Cheng Kung University, No. 1, University Road, Tainan 70101, Taiwan
Funder
Natural Sciences and Engineering Research Council of Canada
Publisher
American Chemical Society (ACS)
Subject
Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.0c04214
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