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On the Performance of Machine Learning Methods for Breakthrough Curve Prediction

Fokina, D, Iliev O, Toktaliev P, Oseledets I, Schindler F

Research article (journal)

Details about the publication

Volume: 2204.11719
Status: submitted / under review
Release year: 2022
Language in which the publication is written: English
DOI: 10.48550/arXiv.2204.11719
Link to the full text: https://arxiv.org/abs/2204.11719

Authors from the University of Münster

Schindler, Felix Tobias
Professorship of Applied Mathematics, especially Numerics (Prof. Ohlberger)

Projects the publication originates from

ML-MORE: Machine learning and model order reduction to predict the efficiency of catalytic filters. Subproject 1: Model Order Reduction (ML-MORE)
Duration: 01/04/2020 - 31/12/2023
Funded by: Federal Ministry of Research, Technology and Space
Type of project: Participation in federally funded joint project
EXC 2044 - C4: Geometry-based modelling, approximation, and reduction
Duration: 01/01/2019 - 31/12/2025 | 1st Funding period
Funded by: DFG - Cluster of Excellence
Type of project: Subproject in DFG-joint project hosted at University of Münster