Online Pentane Concentration Prediction System Based on Machine Learning Techniques
Author:
Affiliation:
1. TECNALIA, Basque Research & Technology Alliance (BRTA), Technological Park of Bizkaia, 48160 Derio, Spain
2. Petronor Innovación S.L, 48550 Muskiz, Spain
Publisher
MDPI
Link
https://www.mdpi.com/2673-4591/39/1/77/pdf
Reference8 articles.
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3. Design and Implementation of hybrid modeling and PFC for oxygen content regulation in a coke furnace;Zhang;IEEE Trans. Ind. Inform.,2018
4. Wang, K., Shang, C., Yang, F., Jiang, Y., and Huang, D. (2017, January 5–8). Automatic hyper-parameter tuning for soft sensor modeling based on dynamic deep neural network. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), Banff, AB, Canada.
5. Niño-Adan, I., Landa-Torres, I., Manjarres, D., Portillo, E., and Orbe, L. (2021). Soft-Sensor for Class Prediction of the Percentage of Pentanes in Butane at a Debutanizer Column. Sensors, 21.
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