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Predictive and prescriptive analytics in transportation geotechnics: Three case studies

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Detalhes bibliográficos
Resumo: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.
Autores principais:Tinoco, Joaquim Agostinho Barbosa
Outros Autores:Parente, Manuel; Correia, António Gomes; Cortez, Paulo; Toll, David
Assunto:Transportation Infrastructures Machine Learning Metaheuristics Earthworks Soil Improvement Slope Stability
Ano:2021
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho

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