Παρακολούθηση
Sindre Stenen Blakseth
Sindre Stenen Blakseth
PhD Candidate, Norwegian University of Science and Technology / Master of Science, SINTEF Energy
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα sintef.no
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Unsupervised Anomaly Detection for IoT-Based Multivariate Time Series: Existing Solutions, Performance Analysis and Future Directions
MA Belay, SS Blakseth, A Rasheed, P Salvo Rossi
Sensors 23 (5), 2844, 2023
582023
Deep neural network enabled corrective source term approach to hybrid analysis and modeling
SS Blakseth, A Rasheed, T Kvamsdal, O San
Neural Networks 146, 181-199, 2022
452022
Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach
SS Blakseth, A Rasheed, T Kvamsdal, O San
Applied Soft Computing 128, 109533, 2022
392022
Introducing CoSTA: A Deep Neural Network Enabled Approach to Improving Physics-Based Numerical Simulations
SS Blakseth
NTNU, 2021
62021
Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions
S Sørbø, SS Blakseth, A Rasheed, T Kvamsdal, O San
Applied Soft Computing 153, 111312, 2024
22024
Enhancing Elasticity Models: A Novel Corrective Source Term Approach for Accurate Predictions
S Sørbø, SS Blakseth, A Rasheed, T Kvamsdal, O San
arXiv preprint arXiv:2309.10181, 2023
2023
Hybrid Dynamic Surrogate Modelling for a Once-Through Steam Generator
SS Blakseth, LE Andersson, RM Montañés, MJ Mazzetti
Computer Aided Chemical Engineering 52, 831-836, 2023
2023
Improving Erroneous Physics-Based Models Using the Corrective Source Term Approach
S Sørbø, SS Blakseth, A Rasheed, T Kvamsdal, O San
Available at SSRN 4269479, 0
Δεν είναι δυνατή η εκτέλεση της ενέργειας από το σύστημα αυτή τη στιγμή. Προσπαθήστε ξανά αργότερα.
Άρθρα 1–8