@article{MTMT:34749014,
	title = {Using dispersion models at microscale to assess long-term air pollution in urban hot spots: A FAIRMODE joint intercomparison exercise for a case study in Antwerp},
	url = {https://m2.mtmt.hu/api/publication/34749014},
	author = {Martín, F. and Janssen, S. and Rodrigues, V. and Sousa, J. and Santiago, J.L. and Rivas, E. and Stocker, J. and Jackson, R. and Russo, F. and Villani, M.G. and Tinarelli, G. and Barbero, D. and José, R. San and Pérez-Camanyo, J.L. and Santos, G. Sousa and Bartzis, J. and Sakellaris, I. and Horváth, Zoltán and Környei, László and Liszkai, B. and Kovács, Á. and Jurado, X. and Reiminger, N. and Thunis, P. and Cuvelier, C.},
	doi = {10.1016/j.scitotenv.2024.171761},
	journal-iso = {SCI TOTAL ENVIRON},
	journal = {SCIENCE OF THE TOTAL ENVIRONMENT},
	volume = {925},
	unique-id = {34749014},
	issn = {0048-9697},
	year = {2024},
	eissn = {1879-1026}
}

@article{MTMT:33757334,
	title = {A MILP approach combined with clustering to solve a special petrol station replenishment problem},
	url = {https://m2.mtmt.hu/api/publication/33757334},
	author = {Hajba, Tamás and Horváth, Zoltán and Heitz, Dániel and Psenák, Bálint},
	doi = {10.1007/s10100-023-00849-1},
	journal-iso = {CEJOR},
	journal = {CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH},
	volume = {32},
	unique-id = {33757334},
	issn = {1435-246X},
	abstract = {Vehicle routing problem is a well-known optimization problem in the logistics area. A special case of the vehicle routing problem is the station replenishment problem in which different types of fuel types have to be transported from the depots to the customers. In this paper we study the replenishment problem of a European petrol company. The problem contains several additional constraints such as time windows, different sized compartment vehicles, and restrictions on the vehicles that can serve a customer. We introduce a mixed integer linear programming model of the problem. To reduce the size complexity of the MILP model the customers are clustered and, based on the clusters, additional constraints are added to the MILP model. The resulting MILP model is tested on real problems of the company. The results show that combining the MILP model with clustering improves the effectiveness of the model.},
	year = {2024},
	eissn = {1613-9178},
	pages = {95-107}
}

@CONFERENCE{MTMT:34553354,
	title = {Developing a High Performance Computing Framework for Simulating and Reducing Urban Air Pollution. The HiDALGO Solution},
	url = {https://m2.mtmt.hu/api/publication/34553354},
	author = {Tomaschek, Tamás Attila and Horváth, Zoltán and Környei, László and Kovács, Ákos and Constans, Mátyás},
	booktitle = {XXVIIth World Road Congress Proceedings of the Congress},
	unique-id = {34553354},
	abstract = {Almost the entire global population (99%) breathes unhealthy levels of fine particulate matter and nitrogen dioxide. Bad air quality in many cities results in 4.2 million premature deaths worldwide per year according to WHO reports and more than 344,000 additional premature deaths (PM2.5, NO2, O3 pollutants) across EU-27 member states. One of the most severe pollutant is NO2 of which main producer is the vehicular traffic. EC introduced assessment methods of exposure measurements and set up policies for ensuring citizens with clean air. Since the implementation of the Directive 2008/50/EC, modelling can be used for some assessments. However, air pollution forecasts are provided only to a limited number of cities and with aggregated values only, contrary that very high spatial resolution would be necessary for accurate epidemiology exposure computations. This is requested by the fact that there may be substantial differences between the concentrations of air pollutants over the city: hot spots may arise and stay at certain places regularly resulting high exposure while the overall (average) air quality indicators used in policies, are below policy thresholds.
		The urban air pollution pilot implemented in the framework of HiDALGO project provides policy makers and the society with a computational tool as service that accurately and quickly forecasts air pollution in cities with very high resolution (1-2 meter resolution at street level). Such a tool did not exist before. A complex traffic and air quality monitoring and traffic control system has been developed in the city of Győr (Western Hungary) to both minimize air pollution while considering traffic flow constraints and serve as validation use case of the computational tools. These main goals were achieved by developing a HPC-framework for simulating the air flow in cities by taking into account real 3D geographical information data of the city, applying highly accurate computational fluid dynamics (CFD) simulation on a highly resolved mesh and using weather forecast data as boundary conditions. Dispersion of the vehicular traffic emitted pollutants in the wind field is computed with strong coupling to the airflow computation. Here the emission is computed from the weakly coupled traffic simulations. The elaborated solution is a valuable tool for the European public and experts for high resolution modelling purposes.},
	year = {2023},
	pages = {IP0572},
	orcid-numbers = {Tomaschek, Tamás Attila/0000-0002-9201-3559}
}

@article{MTMT:34162074,
	title = {A physics-based reduced order model for urban air pollution prediction},
	url = {https://m2.mtmt.hu/api/publication/34162074},
	author = {Khamlich, Moaad and Stabile, Giovanni and Rozza, Gianluigi and Környei, László and Horváth, Zoltán},
	doi = {10.1016/j.cma.2023.116416},
	journal-iso = {COMPUT METHOD APPL M},
	journal = {COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING},
	volume = {417},
	unique-id = {34162074},
	issn = {0045-7825},
	year = {2023},
	eissn = {1879-2138},
	orcid-numbers = {Khamlich, Moaad/0000-0002-2000-0206; Stabile, Giovanni/0000-0003-3434-8446; Rozza, Gianluigi/0000-0002-0810-8812}
}

@article{MTMT:34018990,
	title = {Kriging-Assisted Multi-Objective Optimization Framework for Electric Motors Using Predetermined Driving Strategy},
	url = {https://m2.mtmt.hu/api/publication/34018990},
	author = {Istenes, György and Pusztai, Zoltán and Kőrös, Péter and Horváth, Zoltán and Friedler, Ferenc},
	doi = {10.3390/en16124713},
	journal-iso = {ENERGIES},
	journal = {ENERGIES},
	volume = {16},
	unique-id = {34018990},
	issn = {1996-1073},
	abstract = {In this paper, a multi-objective optimization framework for electric motors and its validation is presented. This framework is suitable for the optimization of design variables of electric motors based on a predetermined driving strategy using MATLAB R2019b and Ansys Maxwell 2019 R3 software. The framework is capable of managing a wide range of objective functions due to its modular structure. The optimization can also be easily parallelized and enhanced with surrogate models to reduce the runtime. The framework is validated by manufacturing and measuring the optimized electric motor. The method’s applicability for solving electric motor design problems is demonstrated via the validation process. A test application is also presented, in which the operating points of a predetermined driving strategy provide the input for the optimization. The kriging surrogate model is used in the framework to reduce the runtime. The results of the optimization and the framework’s benefits and drawbacks are discussed through the provided examples, in addition to displaying the properly applicable design processes. The optimization framework provides a ready-to-use tool for optimizing electric motors based on the driving strategy for single- or multi-objective purposes. The applicability of the framework is demonstrated by optimizing the electric motor of a world recorder energy-efficient race vehicle. In this application, the optimization framework achieved a 2% improvement in energy consumption and a 9% increase in speed at a rated DC voltage, allowing the motor to operate at desired working points even with low battery voltage.},
	year = {2023},
	eissn = {1996-1073}
}

@inproceedings{MTMT:34132489,
	title = {A kriging asszisztens algoritmus hatékonyságának vizsgálata különböző tesztfeladatokon},
	url = {https://m2.mtmt.hu/api/publication/34132489},
	author = {Istenes, György and Horváth, Zoltán},
	booktitle = {Mobilitás és környezet JÖVŐFORMÁLÓ JÁRMŰIPARI KUTATÁSOK Konferenciakiadvány 2022. novemberi konferencia},
	unique-id = {34132489},
	year = {2022},
	pages = {68-78}
}

@inproceedings{MTMT:34032760,
	title = {Villamos motor optimalizációhoz alkalmazott végeselemes modell validációja},
	url = {https://m2.mtmt.hu/api/publication/34032760},
	author = {Istenes, György and Horváth, Zoltán},
	booktitle = {„Digitális Járműipari Kutatások a Széchenyi István Egyetemen – Mesterséges Intelligencia a mobilitásban” Konferenciakiadvány 2022. június},
	unique-id = {34032760},
	year = {2022},
	pages = {171-179}
}

@article{MTMT:33211936,
	title = {Response to Artificial intelligence-based colorectal polyp histology prediction using narrow-band image-magnifying colonoscopy: a stepping stone for clinical practice},
	url = {https://m2.mtmt.hu/api/publication/33211936},
	author = {Rácz, István and Horváth, András and Horváth, Zoltán},
	doi = {10.5946/ce.2022.123.1},
	journal-iso = {CLIN ENDOSC},
	journal = {CLINICAL ENDOSCOPY},
	volume = {55},
	unique-id = {33211936},
	issn = {2234-2400},
	year = {2022},
	eissn = {2234-2443},
	pages = {701-702},
	orcid-numbers = {Rácz, István/0000-0001-9740-6995}
}

@inproceedings{MTMT:33099057,
	title = {Multi-objective Optimization of Electric Motors with a Kriging Surrogate Model},
	url = {https://m2.mtmt.hu/api/publication/33099057},
	author = {Istenes, György and Horváth, Zoltán},
	booktitle = {2022 22nd International Symposium on Electrical Apparatus and Technologies (SIELA)},
	doi = {10.1109/SIELA54794.2022.9845694},
	unique-id = {33099057},
	year = {2022},
	pages = {1-4}
}

@article{MTMT:32244938,
	title = {Artificial Intelligence-Based Colorectal Polyp Histology Prediction by Using Narrow-Band Image-Magnifying Colonoscopy},
	url = {https://m2.mtmt.hu/api/publication/32244938},
	author = {Rácz, István and Horváth, András and KRANITZ, Noemi and KISS, Gyongyi and Regoczi, Henriett and Horváth, Zoltán},
	doi = {10.5946/ce.2021.149},
	journal-iso = {CLIN ENDOSC},
	journal = {CLINICAL ENDOSCOPY},
	volume = {55},
	unique-id = {32244938},
	issn = {2234-2400},
	year = {2022},
	eissn = {2234-2443},
	pages = {113-121},
	orcid-numbers = {Rácz, István/0000-0001-9740-6995}
}