|
|
|
|
|
Yuki Wakatsuki, Hideaki Nakane and Tempei Hashino
The increasing frequency of devastating floods from heavy rainfall?associated with climate change?has made river stage prediction more important. For steep, forest-covered mountainous watersheds, deep-learning models may improve prediction of river stage...
ver más
|
|
|
|
|
|
|
|
|
Nuno M. M. Ramos, Joana Maia, Andrea R. Souza, Ricardo M. S. F. Almeida and Luís Silva
Near-infrared (NIR) reflective materials are being developed for mitigating building cooling needs. Their use contributes to broadening the range of colours, responding to the urban aesthetic demand without compromising the building performance. Despite ...
ver más
|
|
|
|
|
|
|
|
|
Alessandro Massaro, Sergio Selicato and Angelo Galiano
This paper is focused on the design and development of a smart and compact electronic control unit (ECU) for the monitoring of a bus fleet. The ECU system is able to extract all vehicle data by the on-board diagnostics-(ODB)-II and SAE J1939 standards. T...
ver más
|
|
|
|
|
|
|
|
|
César Pérez López, María Jesús Delgado Rodríguez and Sonia de Lucas Santos
The goal of the present research is to contribute to the detection of tax fraud concerning personal income tax returns (IRPF, in Spanish) filed in Spain, through the use of Machine Learning advanced predictive tools, by applying Multilayer Perceptron neu...
ver más
|
|
|
|
|
|
|
|
|
Xin Zhou, Peixin Dong, Jianping Xing and Peijia Sun
Accurate prediction of bus arrival times is a challenging problem in the public transportation field. Previous studies have shown that to improve prediction accuracy, more heterogeneous measurements provide better results. So what other factors should be...
ver más
|
|
|
|