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Passive learning to address nonstationarity in virtual flow metering
  applications

Passive learning to address nonstationarity in virtual flow metering applications

7 February 2022
M. Hotvedt
B. Grimstad
Lars Imsland
ArXivPDFHTML

Papers citing "Passive learning to address nonstationarity in virtual flow metering applications"

4 / 4 papers shown
Title
A deep latent variable model for semi-supervised multi-unit soft sensing
  in industrial processes
A deep latent variable model for semi-supervised multi-unit soft sensing in industrial processes
B. Grimstad
Kristian Lovland
Lars Imsland
V. Gunnerud
31
1
0
18 Jul 2024
Multi-unit soft sensing permits few-shot learning
Multi-unit soft sensing permits few-shot learning
B. Grimstad
Fadhil G. Al-Amran
Maitham G. Yousif
31
1
0
27 Sep 2023
Sequential Monte Carlo applied to virtual flow meter calibration
Sequential Monte Carlo applied to virtual flow meter calibration
Anders T. Sandnes
B. Grimstad
O. Kolbjørnsen
18
0
0
13 Apr 2023
Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter -- a
  Case Study
Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter -- a Case Study
M. Hotvedt
B. Grimstad
Lars Imsland
19
22
0
07 Feb 2020
1