Passive learning to address nonstationarity in virtual flow metering applications
Author:
Publisher
Elsevier BV
Subject
Artificial Intelligence,Computer Science Applications,General Engineering
Reference49 articles.
1. AL-Qutami, T. A., Ibrahim, R., & Ismail, I. (2017). Hybrid neural network and regression tree ensemble pruned by simulated annealing for virtual flow metering application.. In IEEE international conference on signal and image processing applications (pp. 304–309).
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3. AL-Qutami, T. A., Ibrahim, R., Ismail, I., & Ishak, M. A. (2017b). Radial basis function network to predict gas flow rate in multiphase flow. In Proceedings of the 9th international conference on machine learning and computing (pp. 141–146).
4. Virtual multiphase flow metering using diverse neural network ensemble and adaptive simulated annealing;AL-Qutami;Expert Systems with Applications,2018
5. Amin, A. (2015). Evaluation of Commercially Available Virtual Flow Meters (VFMs). In Proceedings of the annual offshore technology conference (pp. 1293–1318).
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