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Budapest University of Technology and Economics
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Latest Publications
Journal Article
Communications in Transportation Research
Published: 01 December 2024 in Communications in Transportation Research

Smart mobility solutions are trending in the mobility domain realized through pilot activities and commercial solutions, but there is a lack of a broad framework defining the readiness to introduce such mobility solutions in a specific area. In this research, smart mobility solutions are examined in the perspective of the Mobility-as-a-Service (MaaS) scheme that is an adequate representation of the maturity of a region regarding smart mobility solutions including technology, business, and coopetition aspects. These three aspects define the feature selection, whereas surveys are used to collect input data from local experts (LEs). For weighting the features, the analytic hierarchy process (AHP) is used with a modified interpretive structural modeling (ISM). With this modification, an expert-friendly process is developed without affecting the results. The elaborated MaaS readiness index (MRI) is applied to six regions with different types of mobility related pilot activities to demonstrate the MRI as a comparison tool between regions and between ex-ante and ex-post pilot activities. The developed interpretive structural modeling with Graph (ISM-G) methodology requites remarkably less work from the evaluators compared to the ISM, while no important difference appeared in the results. The MRI can support smart mobility related pilot evaluations, whereas the ISM-G can be used widely in decision-making.

ACS Style

Attila Aba; Domokos Esztergár-Kiss. Creation of the MaaS readiness index with a modified AHP-ISM method. Communications in Transportation Research 2024, 4 .

AMA Style

Attila Aba, Domokos Esztergár-Kiss. Creation of the MaaS readiness index with a modified AHP-ISM method. Communications in Transportation Research. 2024; 4 ():.

Chicago/Turabian Style

Attila Aba; Domokos Esztergár-Kiss. 2024. "Creation of the MaaS readiness index with a modified AHP-ISM method." Communications in Transportation Research 4, no. : .

Journal Article
Annals of Nuclear Energy
Published: 01 September 2024 in Annals of Nuclear Energy

This paper deals with group constant parameterization, a necessary step to utilize the results of assembly-level neutronics calculations at the full-core level. The focus is on low sample size problems when the commonly used linear interpolation approach is inadequate, a typical situation of using Monte Carlo codes for group constant generation. This work presents a newly developed code package for automated group constant parameterization. It implements several machine learning regression models − including a novel polynomial regression algorithm − performs hyperparameter optimization and selects the best model based on a detailed evaluation. The applicability of the new code package is demonstrated in a case study for a VVER-1200 fuel assembly covering both normal operation and transient conditions. In this example, the novel polynomial regression model provides a 73 pcm average error in kinf that leads to reactivity coefficients well within the desired precision.

ACS Style

Dániel Sebestény; István Panka; Bálint Batki. Automated group constant parameterization for low sample sizes using different Machine learning approaches. Annals of Nuclear Energy 2024, 204 .

AMA Style

Dániel Sebestény, István Panka, Bálint Batki. Automated group constant parameterization for low sample sizes using different Machine learning approaches. Annals of Nuclear Energy. 2024; 204 ():.

Chicago/Turabian Style

Dániel Sebestény; István Panka; Bálint Batki. 2024. "Automated group constant parameterization for low sample sizes using different Machine learning approaches." Annals of Nuclear Energy 204, no. : .

Journal Article
Applied Mathematics and Computation
Published: 01 August 2024 in Applied Mathematics and Computation
ACS Style

András Mészáros; Miklós Telek. Numerical inverse transformation of double sided Laplace transform with parameter optimization. Applied Mathematics and Computation 2024, 474 .

AMA Style

András Mészáros, Miklós Telek. Numerical inverse transformation of double sided Laplace transform with parameter optimization. Applied Mathematics and Computation. 2024; 474 ():.

Chicago/Turabian Style

András Mészáros; Miklós Telek. 2024. "Numerical inverse transformation of double sided Laplace transform with parameter optimization." Applied Mathematics and Computation 474, no. : .

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Date: 8–9 October 2021