# Reconstruction of Epidemiological Data in Hungary Using Stochastic Model Predictive Control
## Abbreviations
Available online: [[http://casadi.sourceforge.net/v3.4.4/users_guide/casadi-users_guide.pdf](http://casadi.sourceforge.net/v3.4.4/users_guide/casadi-users_guide.pdf)]([http://casadi.sourceforge.net/v3.4.4/users_guide/casadi-users_guide.pdf](http://casadi.sourceforge.net/v3.4.4/users_guide/casadi-users_guide.pdf)) (accessed on 17 December 2021). * [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] CasADi: A software framework for nonlinear optimization and optimal control. _Math. Program. Comput._**2018**, _11_, 1-36. [CrossRef]
* [PERSON] (2005) [PERSON]; [PERSON] [PERSON] On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming. _Math. Program._**2005**, _106_, 25-57. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] Forces NLP: An efficient implementation of interior-point methods for multistage nonlinear nonconvex programs. _Int. J. Control_**2017**, _93_, 13-29. [CrossRef]
* [PERSON] (2016) [PERSON] Stochastic model predictive control: An overview and perspectives for future research. _IEEE Control. Syst. Mag._**2016**, _36_, 304-44. [CrossRef]
* [PERSON] et al. (2005) [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Stochastic programming applied to model predictive control. In Proceedings of the 44 th IEEE Conference on Decision and Control, Seville, Spain, 15 December 2005; pp. 1361-1366. [CrossRef]
* [PERSON] and [PERSON] (2012) [PERSON]; [PERSON] [PERSON] Stabilizing model predictive control of stochastic constrained linear systems. _IEEE Trans. Autom. Control_**2012**, _57_, 1468-1480. [CrossRef]
* [PERSON] and [PERSON] (2020) [PERSON]; [PERSON]; [PERSON] Robust multi-stage nonlinear model predictive control using sigma points. _Processes_**2020**, \(8\), 851. [CrossRef]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON] Dual multi-stage NMPC using sigma point principles. _IFAC-PapersOnLine_**2020**, _53_, 11243-11250. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Fast approximate learning-based multistage nonlinear model predictive control using Gaussian processes and deep neural networks. _Comput. Chem. Eng._**2021**, _145_, 107174. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON] Conservative to confident: Treating uncertainty robustly within learning-based control. In Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 26-30 May 2015; pp. 421-427. [CrossRef]
* [PERSON] et al. (2020) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] Cautious model predictive control using Gaussian process regression. _IEEE Trans. Control. Syst. Technol._**2020**, _28_, 2736-2743. [CrossRef]
* [PERSON] et al. (2003) [PERSON] [PERSON]; [PERSON]; [PERSON] _Prediction at an Uncertain Input for Gaussian Processes and Relevance Vector Machines Application to Multiple-Step Ahead Time-Series Forecasting_; Technical Report IMM-2003-18; Technical University of Denmark: Kgs. Lyngby, Denmark, 2003. * [PERSON] (2017) [PERSON] Efficient Reinforcement Learning Using Gaussian Processes--Revised Version. Ph.D. Thesis, Faculty of Informatics, Institute for Anthropomatics, Intelligent Sensor-Actuator-Systems Laboratory (ISAS), Karlsruhe, Germany, 2017. * [PERSON] et al. (2020) [PERSON] [PERSON]; [PERSON]; [PERSON], [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON], [PERSON]; et al. Diagnostic characteristics of serological-based COVID-19 testing: A systematic review and meta-analysis. _Clintics_**2020**, _75_, e2212. [CrossRef] [PubMed]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; et al. Novel coronavirus epidemic in the Hungarian population, a cross-sectional nationwide survey to support the exit policy in Hungary. _Gerscience_**2020**, _42_, 1063-1074. [CrossRef]
* [PERSON] et al.