Maximizing information from chemical engineering data sets: Applications to machine learning (2022)
Attributed to:
GALINI: Global ALgorithms for mixed-Integer Nonlinear optimisation of Industrial systems
funded by
EPSRC
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.1016/j.ces.2022.117469
Publication URI: http://dx.doi.org/10.1016/j.ces.2022.117469
Type: Journal Article/Review
Parent Publication: Chemical Engineering Science