2026-07-31T20:27:48Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/68762024-05-20T09:52:07Zcom_10259.4_104com_10259_2604col_10259_6848
Cardona, John F.
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600
Castaneda, Juliana
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600
Martins, Leandro do C.
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600
Gandouz, Mariem
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600
Juan, Angel A.
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600
Franco, Guillermo
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600
2022-09-16T07:08:08Z
2022-09-16T07:08:08Z
2021-07
978-84-18465-12-3
http://hdl.handle.net/10259/6876
10.36443/10259/6876
Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos
This paper discusses a case study in which publicly available data of a rail freight
transportation firm has been gathered, cleansed, and analyzed in order to: (i) describe the
data using statistical indicators and graphs; (ii) identify patterns regarding several Key
Performance Indicators; (iii) obtain forecasts on the future evolution of these indicators; and
(iv) use the identified patterns and the generated forecasts to propose customized insurance
products that reflect the current and future freight transportation activity. The paper
illustrates the different methodological steps required during the extraction and cleansing of
the data --which required the development of Python scripts--, the use of time series analysis
for obtaining reliable forecasts, and the use of machine learning models for designing
customized insurance coverage from the identified patterns and predicted values.
This study was collectively completed and supported by Guy Carpenter & Company, LLC, and the Universitat Oberta de Catalunya.
application/pdf
eng
Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional
R-Evolucionando el transporte
http://hdl.handle.net/10259/6490
https://doi.org/10.36443/9788418465123
Ferrocarriles
Railways
Ingeniería civil
Transportes
Civil engineering
Transportation
Using Data Analytics & Machine Learning to Design Business Interruption Insurance Products for Rail Freight Operators
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license.txt
license.txt
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Cardona_CIT2021_487-504.pdf
Cardona_CIT2021_487-504.pdf
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10259/6876
oai:riubu.ubu.es:10259/6876
2024-05-20 11:52:07.396
Repositorio Institucional de la Universidad de Burgos
bubrep@ubu.es
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