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Pedro Nogueira, Marcelo Silva, Paulo Infante, Vitor Nogueira, Paulo Manuel, Anabela Afonso, Gonçalo Jacinto, Leonor Rego, Paulo Quaresma, José Saias, Daniel Santos and Patricia Gois
Road traffic accidents are a major concern for modern society with a high toll on human life and involve hard to account economic consequences. New knowledge can be obtained from combining GIS tools with machine learning and artificial intelligence, deve...
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Alessandro Rasulo, Sofia Nardoianni, Azzurra Evangelisti and Mauro D?Apuzzo
Transportation networks are one of the most vulnerable civil infrastructures during an earthquake and an estimation of traffic impacts in the post-earthquake scenario is a crucial aspect in the context of risk assessment and evaluation of remedial measur...
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Higor Costa de Brito, Iana Alexandra Alves Rufino, Mauro Normando Macedo Barros Filho and Ronaldo Amâncio Meneses
In the face of urban expansion, ensuring sustainable water consumption is paramount. This study aims to develop a domestic water demand forecast model that considers population heterogeneity and the urban area distribution in a city in the Brazilian Semi...
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Yacine Mohia, Rafik Absi, Mourad Lazri, Karim Labadi, Fethi Ouallouche and Soltane Ameur
To estimate rainfall from remote sensing data, three machine learning-based regression models, K-Nearest Neighbors Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were implemented using MSG (Meteosat Second Genera...
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Ivan Kovac, Marko ?rajbek, Nikolina Kli?anin and Gordon Gilja
The localization of pollution sources is one of the main tasks in environmental engineering. For this paper, models of spatial distribution of nitrate concentration in groundwater were created, and the point of highest concentration was determined. This ...
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