Position:
Researcher
PhD student
Department:
Department of Information Engineering and Process Control (DIEPC)
Room:
NB 647
eMail:
Home page:
https://www.uiam.sk/~mojto
Phone:
+421 259 325 349
ORCID iD:
0000-0002-6114-2710
WoS ResearcherID:
AAZ-3608-2020
Google Scholar:
sjBbi0AAAAAJ
Availability:

Publications

Article in journal

  1. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-Based Design of Multi-Model Inferential Sensors. Computers & Chemical Engineering, vol. 178, 2023.   arXiv   Zenodo
  2. M. Mojto – M. HorváthováK. Kiš – M. Furka – M. Bakošová: Predictive control of a cascade of biochemical reactors. Acta Chimica Slovaca, no. 1, vol. 14, pp. 51–59, 2021.
  3. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-based design of inferential sensors for petrochemical industry. Computers & Chemical Engineering, vol. 153, pp. 107437, 2021.   arXiv

Article in conference proceedings

  1. R. Fáber – K. Ľubušký – M. Mojto – R. Paulen: Enhancing Industrial Data Analysis through Machine Learning-based Classification of Petrochemical Datasets. In 49th International Conference of the Slovak Society of Chemical Engineering SSCHE 2023, Slovak Society of Chemical Engineering, Bratislava, SK, pp. 160–160, 2023.   Zenodo
  2. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Comparing Linear and Nonlinear Soft Sensor Approaches for Industrial Distillation Columns (in Anglo-Saxon). In 49th International Conference of the Slovak Society of Chemical Engineering SSCHE 2023, Slovak Society of Chemical Engineering, Bratislava, SK, pp. 159–159, 2023.   Zenodo
  3. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Input Structure Selection for Soft-Sensor Design: Does It Pay Off?. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 2023 24th International Conference on Process Control, IEEE, Slovak University of Technology in Bratislava, Radlinského 9, 81237, Bratislava, Slovakia, pp. 162–167, 2023.   Zenodo
  4. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-Driven Indication of Flooding in an Industrial Debutanizer Column. Editor(s): Antonis Kokossis, Michael C. Georgiadis, Efstratios N. Pistikopoulos, In 33rd European Symposium on Computer Aided Process Engineering, Elsevier, no. 1, vol. 33, pp. 1001–1006, 2023.   Zenodo
  5. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Design of Multi-Model Linear Inferential Sensors with SVM-based Switching Logic. In IFAC World Congress 2023, Yokohama, Japan, pp. 2545–2550, 2023.     Zenodo
  6. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-based Design of Inferential Sensors for an Industrial Depropanizer Column with Data Pre-treatment Analysis. Editor(s): Mário Mihaľ, In 48th International Conference of the Slovak Society of Chemical Engineering SSCHE 2022 and Membrane Conference PERMEA 2022, Slovak Society of Chemical Engineering, Bratislava, SK, pp. 200, 2022.
  7. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Support Vector Machine-based Design of Multi-model Inferential Sensors. Editor(s): Ludovic Montastruc, Stephane Negny, In 32nd European Symposium on Computer Aided Process Engineering, Elsevier, no. 1, vol. 32, pp. 1045–1050, 2022.
  8. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Multi-Model Soft-Sensor Design for a Depropanizer Distillation Column. In Advanced Process Modelling Forum 18-19 October 2022, 2022.   Zenodo
  9. M. Fikar – M. Furka – M. HorváthováK. Kiš – M. Mojto: Dynamic Optimisation Toolbox dynopt 5.0. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 23rd International Conference on Process Control, IEEE, Slovak University of Technology, pp. 296–301, 2021.
  10. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data Treatment of Industrial Measurements: From Online to Inferential Sensors. Editor(s): R. Paulen, M. Fikar and J. Oravec, In Proceedings of the 23rd International Conference on Process Control - Summaries Volume, Slovak Chemical Library, Slovak University of Technology in Bratislava, Radlinského 9, SK812-37, Bratislava, Slovakia, pp. 52–53, 2021.
  11. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-based Industrial Soft-sensor Design via Optimal Subset Selection. Editor(s): Metin Türkay, Rafiqul Gani, In 31st European Symposium on Computer Aided Process Engineering, Elsevier, vol. 31, pp. 1247–1252, 2021.
  12. M. Furka – K. KišM. Horváthová – M. Mojto – M. Bakošová: Identification and Control of a Cascade of Biochemical Reactors. In 2020 Cybernetics & Informatics (K&I), 2020.
  13. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Advanced Process Control of an Industrial Depropanizer Column using Data-based Inferential Sensors. Editor(s): Sauro Pierucci, Flavio Manenti, Giulia Luisa Bozzano, Davide Manca, In 30th European Symposium on Computer Aided Process Engineering, Elsevier, vol. 30, pp. 1213–1218, 2020.
  14. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Design of Data-based Inferential Sensors for Industrial Depropanizer Column. Editor(s): G. Léonard and F. Logist, In Computer Aided Process Engineering, CAPE Forum, pp. 12–13, 2019.
  15. M. Mojto – K. Ľubušký – R. PaulenM. Fikar: Advanced Process Control of a Depropanizer Column. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
  16. M. Mojto – R. Paulen – K. Ľubušký – M. Fikar: Modelling and Analysis of Control Pairings of an Industrial Depropanizer Column. In Advanced Process Modelling Forum 26-27 March 2019, pp. 5–6, 2019.

Phd's thesis

  1. M. Mojto: Data-driven Design of Linear Soft Sensors (pre-defense). 2023.

Master's thesis

  1. M. Mojto: Advanced Process Control of a Depropanizer Column. Master's thesis, ÚIAM FCHPT STU v Bratislave, Radlinského 9, 812 37 Bratislava, 2019.

Miscellaneous

  1. M. Mojto: Data-based Design of Inferential Sensors for Petrochemical Industry. 2021.   arXiv
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