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Artículo
Explaining deep learning models for ozone pollution prediction via embedded feature selection
(ScienceDirect, 2024)
Ambient air pollution is a pervasive global issue that poses significant health risks. Among pollutants, ozone (O3) is responsible for an estimated 1 to 1.2 million premature deaths yearly. Furthermore, O3 adversely affects ...
Artículo
Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection
(Elsevier, 2012)
Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature ...
Artículo
Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula
(Elsevier, 2013)
This work explores the use of different seismicity indicators as inputs for artificial neural networks. The combination of multiple indicators that have already been successfully used in different seismic zones by the ...
Artículo
A coral-reef approach to extract information from HTML tables
(Elsevier, 2022)
his article presents Coraline, which is a new table-understanding proposal. Its novelty lies in a coral-reef optimisation algorithm that addresses the problem of feature selection in synchrony with a clustering technique ...
Artículo
An adaptive methodology to discretize and select features
(SciEdu Press, 2013)
A lot of significant data describing the behavior or/and actions of systems can be collected in several domains. These data define some aspects, called features, that can be clustered in several classes. A qualitative or ...