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U.S. Department of Energy
Office of Scientific and Technical Information

MINLP for regularized symbolic regression with applications to data-driven modeling of critical minerals processes

Conference ·
DOI:https://doi.org/10.2172/3027686· OSTI ID:3027686
The poster summarizes recent advances in symbolic regression developed as part of the PrOMMiS project over the past year. In particular, it describes the comparison of surrogates for critical minerals (CM) & rare earth element (REE) recovery flowsheets obtained via symbolic regression and ALAMO. It also compares the predictive ability and solvability of optimization models that incorporate these surrogates.
Research Organization:
National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)
Sponsoring Organization:
USDOE Office of Fossil Energy and Carbon Management (FECM); USDOE Office of Fossil Energy and Carbon Management (FECM), Office of Resource Sustainability (FE-30)
DOE Contract Number:
;
OSTI ID:
3027686
Resource Type:
Conference poster
Conference Information:
Conference Name: ACS Spring 2026 Location: Atlanta, GA, United States Start Date: 3/22/2026 12:00:00 AM End Date: 3/26/2026 12:00:00 AM
Country of Publication:
United States
Language:
English