Simple Non Regressive Informed Machine Learning Model for Prescriptive Maintenance of Track Circuits in a Subway Environment

Autor: Andrea Garrone, Simone Minisi, Luca Oneto, Carlo Dambra, Marco Borinato, Paolo Sanetti, Giulia Vignola, Federico Papa, Nadia Mazzino, Davide Anguita

Publikováno v: Lecture Notes in Networks and Systems ISBN: 9783031162800

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11bdeb22f2b73d654f28a6960487f87e
https://doi.org/10.1007/978-3-031-16281-7_8

Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability

Autor: Simone Petralli, Renzo Canepa, Luca Oneto, Paolo Sanetti, Irene Buselli, Davide Anguita

Publikováno v: Recent Advances in Big Data and Deep Learning-Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019
Proceedings of the International Neural Networks Society
Proceedings of the International Neural Networks Society-Recent Advances in Big Data and Deep Learning
Proceedings of the International Neural Networks Society ISBN: 9783030168407
INNSBDDL

Every time an asset of a large scale railway network is affected by a failure or maintained, it will impact not only the single asset functional behaviour but also the normal execution of the railway operations and trains circulation. In this framewo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67a84709de7812eb6cc08035e802007b

On Applying Machine Learning and Simulative Approaches to Railway Asset Management: The Earthworks and Track Circuits Case Studies

Autor: José Solís-Hernández, Iñigo Mingolarra-Garaizar, Noemi Jiménez-Redondo, Alice Consilvio, Federico Papa, Paolo Sanetti

Publikováno v: Sustainability
Volume 12
Issue 6
Sustainability, Vol 12, Iss 6, p 2544 (2020)

The objective of this study is to show the applicability of machine learning and simulative approaches to the development of decision support systems for railway asset management. These techniques are applied within the generic framework developed an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e23e8bfe85269343656ac9133c46d05c
https://doi.org/10.3390/su12062544

Marine safety and data analytics : vessel crash stop maneuvering performance prediction

Autor: Davide Anguita, Andrea Coraddu, Olena Karpenko, Luca Oneto, Paolo Sanetti, Toine Cleophas, Francesca Cipollini

Publikováno v: Artificial Neural Networks and Machine Learning – ICANN 2017 ISBN: 9783319686110
ICANN (2)

Crash stop maneuvering performance is one of the key indicators of the vessel safety properties for a shipbuilding company. Many different factors affect these performances, from the vessel design to the environmental conditions, hence it is not triv

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1248a6b557d28378fd7b645686cf2a4d
https://strathprints.strath.ac.uk/64250/1/Oneto_etal_ICANN_2017_Marine_safety_and_data_analytics_vessel_crash_stop_maneuvering_performance_prediction.pdf