Pracovné zaradenie:
Vedecko-výskumný pracovník
Doktorand
Oddelenie:
Oddelenie informatizácie a riadenia procesov (OIaRP)
Miestnosť:
NB 647
eMail:
Webová stránka:
https://www.uiam.sk/~mojto
Telefón:
+421 259 325 349
ORCID iD:
0000-0002-6114-2710
WoS ResearcherID:
AAZ-3608-2020
Google Scholar:
sjBbi0AAAAAJ
Dostupnosť:

Publikácie

Článok v časopise

  1. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-Based Design of Multi-Model Inferential Sensors. Computers & Chemical Engineering, zv. 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, č. 1, zv. 14, str. 51–59, 2021.
  3. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-based design of inferential sensors for petrochemical industry. Computers & Chemical Engineering, zv. 153, str. 107437, 2021.   arXiv

Príspevok na konferencii

  1. R. Fáber – K. Ľubušký – M. Mojto – R. Paulen: Enhancing Industrial Data Analysis through Machine Learning-based Classification of Petrochemical Datasets. V 49th International Conference of the Slovak Society of Chemical Engineering SSCHE 2023, Slovak Society of Chemical Engineering, Bratislava, SK, str. 160–160, 2023.   Zenodo
  2. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Comparing Linear and Nonlinear Soft Sensor Approaches for Industrial Distillation Columns. V 49th International Conference of the Slovak Society of Chemical Engineering SSCHE 2023, Slovak Society of Chemical Engineering, Bratislava, SK, str. 159–159, 2023.   Zenodo
  3. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Input Structure Selection for Soft-Sensor Design: Does It Pay Off?. Editor(i): R. Paulen and M. Fikar, V Proceedings of the 2023 24th International Conference on Process Control, IEEE, Slovak University of Technology in Bratislava, Radlinského 9, 81237, Bratislava, Slovakia, str. 162–167, 2023.   Zenodo
  4. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-Driven Indication of Flooding in an Industrial Debutanizer Column. Editor(i): Antonis Kokossis, Michael C. Georgiadis, Efstratios N. Pistikopoulos, V 33rd European Symposium on Computer Aided Process Engineering, Elsevier, č. 1, zv. 33, str. 1001–1006, 2023.   Zenodo
  5. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Design of Multi-Model Linear Inferential Sensors with SVM-based Switching Logic. V IFAC World Congress 2023, Yokohama, Japan, str. 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(i): Mário Mihaľ, V 48th International Conference of the Slovak Society of Chemical Engineering SSCHE 2022 and Membrane Conference PERMEA 2022, Slovak Society of Chemical Engineering, Bratislava, SK, str. 200, 2022.
  7. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Support Vector Machine-based Design of Multi-model Inferential Sensors. Editor(i): Ludovic Montastruc, Stephane Negny, V 32nd European Symposium on Computer Aided Process Engineering, Elsevier, č. 1, zv. 32, str. 1045–1050, 2022.
  8. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Multi-Model Soft-Sensor Design for a Depropanizer Distillation Column. V 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(i): R. Paulen and M. Fikar, V Proceedings of the 23rd International Conference on Process Control, IEEE, Slovak University of Technology, str. 296–301, 2021.
  10. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data Treatment of Industrial Measurements: From Online to Inferential Sensors. Editor(i): R. Paulen, M. Fikar and J. Oravec, V 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, str. 52–53, 2021.
  11. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-based Industrial Soft-sensor Design via Optimal Subset Selection. Editor(i): Metin Türkay, Rafiqul Gani, V 31st European Symposium on Computer Aided Process Engineering, Elsevier, zv. 31, str. 1247–1252, 2021.
  12. M. Furka – K. KišM. Horváthová – M. Mojto – M. Bakošová: Identification and Control of a Cascade of Biochemical Reactors. V 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(i): Sauro Pierucci, Flavio Manenti, Giulia Luisa Bozzano, Davide Manca, V 30th European Symposium on Computer Aided Process Engineering, Elsevier, zv. 30, str. 1213–1218, 2020.
  14. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Design of Data-based Inferential Sensors for Industrial Depropanizer Column. Editor(i): G. Léonard and F. Logist, V Computer Aided Process Engineering, CAPE Forum, str. 12–13, 2019.
  15. M. Mojto – K. Ľubušký – R. PaulenM. Fikar: Advanced Process Control of a Depropanizer Column. Editor(i): M. Fikar and M. Kvasnica, V 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. V Advanced Process Modelling Forum 26-27 March 2019, str. 5–6, 2019.

Dizertačná práca

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

Diplomová práca

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

Rôzne

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