Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/74076

TítuloPredictive and prescriptive analytics in transportation geotechnics: Three case studies
Autor(es)Tinoco, Joaquim Agostinho Barbosa
Parente, Manuel
Correia, António Gomes
Cortez, Paulo
Toll, David
Palavras-chaveTransportation Infrastructures
Machine Learning
Metaheuristics
Earthworks
Soil Improvement
Slope Stability
DataSet-2021
EditoraElsevier 1
RevistaTransportation Engineering
CitaçãoTinoco, J., Parente, M., Correia, A. G., Cortez, P., & Toll, D. (2021). Predictive and Prescriptive Analytics in Transportation Geotechnics: Three Case studies. Transportation Engineering
Resumo(s)Transportation infrastructure is of paramount importance for any country. The construction, management and maintenance of this infrastructure is a complex task that requires a significant amount of resources (e.g., human work equipment, materials, maintenance costs). To better support this task, in the last decades several Artificial Intelligence (AI) data analysis tools have been proposed. In this paper, we summarize recent predictive and prescriptive AI applications to the transportation infrastructure field, underlying their strategic impact. In particular, we discuss three case studies: the design of better earthwork projects; the prediction of jet grouting soilcrete mechanical and physical properties (uniaxial compressive strength, stiffness and column diameter); and prediction of the stability level of engineered slopes.
TipoArtigo
URIhttps://hdl.handle.net/1822/74076
DOI10.1016/j.treng.2021.100074
ISSN2666-691X
Versão da editorahttps://www.sciencedirect.com/science/article/pii/S2666691X21000300
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals
ISISE - Artigos em Revistas Internacionais

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