ARtificial Intelligence and STOchasTic Simulation for the rEsiLience of Critical InfrastructurES (ARISTOTELES)

In this paper, we present the ambitions of the research project ARtificial Intelligence and STOchasTic simulation for the rEsiLience of critical infrastructurES (ARISTOTELES), funded by the Italian Ministry for Scientific Research (MIUR) under the PRIN 2022 program (grant 2022TAFXZ5) and by the European Union - Next Generation EU program. The aim is to share the objectives and preliminary results, for fostering further collaboration.

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Publication Details

Published
2024-11-20
DOI
https://doi.org/10.1109/icsrs63046.2024.10927422
Citations
2
Primary Topic
Simulation Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.98
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article

ARtificial Intelligence and STOchasTic Simulation for the rEsiLience of Critical InfrastructurES (ARISTOTELES)

Enrico Zio, Matteo Taroni, Francesco Di Maio, Nicola Pedroni
2 citations
Simulation Techniques and Applications
0.98
article

ARtificial Intelligence and STOchasTic Simulation for the rEsiLience of Critical InfrastructurES (ARISTOTELES)

Enrico Zio, Matteo Taroni, Francesco Di Maio, Nicola Pedroni
article en
2 citations

Abstract

In this paper, we present the ambitions of the research project ARtificial Intelligence and STOchasTic simulation for the rEsiLience of critical infrastructurES (ARISTOTELES), funded by the Italian Ministry for Scientific Research (MIUR) under the PRIN 2022 program (grant 2022TAFXZ5) and by the European Union - Next Generation EU program. The aim is to share the objectives and preliminary results, for fostering further collaboration.

Politecnico di Torino (IT), Istituto Nazionale di Geofisica e Vulcanologia (IT), Politecnico di Milano (IT)
Industry, innovation and infrastructure
Openalex Percentile: Top 19%
Simulation Techniques and Applications
0.98
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ARtificial Intelligence and STOchasTic Simulation for the rEsiLience of Critical InfrastructurES (ARISTOTELES) — Enrico Zio, Matteo Taroni, et al. · (2024) | TGRS Research Map | TGRS