Soft-sensors based on Black-box Models for Bioreactors Monitoring and State Estimation-Reference-Cited by-同舟云学术

Soft-sensors based on Black-box Models for Bioreactors Monitoring and State Estimation

Published:2020-05-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 12th International Conference on Bioinformatics and Biomedical Technology
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Author:

Vaitkus Vygandas¹,Brazauskas Kęstutis¹,Repšytė Jolanta¹

Affiliation:

1. Automation Department, Kaunas University of Technology, Kaunas LT, Lithuania

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3405758.3405780

Reference17 articles.

1. B Sonnleitner 1999 Instrumentation of biotechnological processes in Advances in Biochemical Engineering and Biotechnology Springer 3--54. B Sonnleitner 1999 Instrumentation of biotechnological processes in Advances in Biochemical Engineering and Biotechnology Springer 3--54.

2. CF Mandenius 2004 Recent developments in the monitoring modeling and control of biological production systems Bioproc. Biosyst. Eng vol 26 pp 347--351. CF Mandenius 2004 Recent developments in the monitoring modeling and control of biological production systems Bioproc. Biosyst. Eng vol 26 pp 347--351.

3. R Simutis V Galvanauskas D Levisauskas J Repsyte and V Vaitkus 2013 Comparative Study of Intelligent Soft-Sensors for Bioprocess State Estimation. JOLST 163--167. R Simutis V Galvanauskas D Levisauskas J Repsyte and V Vaitkus 2013 Comparative Study of Intelligent Soft-Sensors for Bioprocess State Estimation. JOLST 163--167.

4. Data-driven Soft Sensors in the process industry

5. A soft sensor based on adaptive fuzzy neural network and support vector regression for industrial melt index prediction

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