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Publication Year: 2026

61 to 70 of 550 Results

00_ReadMe.txt Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production Plain Text - 4.1 KB - MD5: d876283a934a820f7703dd26e950e133
calculate_output.m Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production MATLAB Source Code - 459 B - MD5: bfc538b18e25ef6c92be4f828244e4a7
make_w_gc.m Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production MATLAB Source Code - 1.1 KB - MD5: 61bda33eb19fff36c06dc94044f2e65a
ML_dev_part1.ipynb Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production Jupyter Notebook - 255.9 KB - MD5: 15e085e50a122a36c8cc28635f956db7
ML_dev_part2.ipynb Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production Jupyter Notebook - 240.4 KB - MD5: aec99d2af4b73cb120944552410a6f16
oil_field_model.m Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production MATLAB Source Code - 4.2 KB - MD5: 3afdf981934adb3916a638c92b3e0ef4
openloop_simulation.m Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production MATLAB Source Code - 4.4 KB - MD5: ab8287accb12c0c577c099c750b6910e
Readme.md Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production Markdown Text - 155 B - MD5: 0c05268200c7ad6592a1f7d9edf5d792
update_states.m Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production MATLAB Source Code - 319 B - MD5: 22c8cc35407cf3e6460003bceedc8911
Replication data for: Real-Time Optimization and Estimation for CO2 Purification Process Feb 24, 2026 - University of South-Eastern Norway Hvidsten, Jan Inge; Mirlekar, Gaurav, 2026, "Replication data for: Real-Time Optimization and Estimation for CO2 Purification Process", https://doi.org/10.18710/UFXAVM, DataverseNO, V1 The dataset represents dynamic simulation and estimation data for a CO2 scrubbing process in a bio‑CO2 purification plant, used to design and test a real‑time optimization and Kalman filter–based control framework for solvent flow. Purpose: To estimate unmeasured mass flows (CO2 inlet gas flow and rich solvent flow) in a CO2 scrubber using first‑ a...

00_ReadMe.txt

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

Plain Text - 4.1 KB -

calculate_output.m

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

MATLAB Source Code - 459 B -

make_w_gc.m

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

MATLAB Source Code - 1.1 KB -

ML_dev_part1.ipynb

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

Jupyter Notebook - 255.9 KB -

ML_dev_part2.ipynb

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

Jupyter Notebook - 240.4 KB -

oil_field_model.m

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

MATLAB Source Code - 4.2 KB -

openloop_simulation.m

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

MATLAB Source Code - 4.4 KB -

Readme.md

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

Markdown Text - 155 B -

update_states.m

Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production

MATLAB Source Code - 319 B -

Replication data for: Real-Time Optimization and Estimation for CO2 Purification Process

Feb 24, 2026 - University of South-Eastern Norway

Hvidsten, Jan Inge; Mirlekar, Gaurav, 2026, "Replication data for: Real-Time Optimization and Estimation for CO2 Purification Process", https://doi.org/10.18710/UFXAVM, DataverseNO, V1

The dataset represents dynamic simulation and estimation data for a CO2 scrubbing process in a bio‑CO2 purification plant, used to design and test a real‑time optimization and Kalman filter–based control framework for solvent flow. Purpose: To estimate unmeasured mass flows (CO2 inlet gas flow and rich solvent flow) in a CO2 scrubber using first‑ a...

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