A Multi-Aspect Feature Dependency Screening for Augmentation of Derivative Feature Space Boosting Deep Learning Training: A Case of Air Quality in Subtropical Areas

This study examines the application of deep learning (DL) in predicting multivariate time-series (MTS), emphasizing the significance of novel feature exploration for intensive model re-training. This approach is essential for adaptive feature engineering, as the numerical properties of the foundatio...

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Autores principales:	Benedito Chi Man Tam, Su-Kit Tang, Alberto Cardoso
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	IEEE 2026-01-01
Colección:	IEEE Access
Materias:	Air quality prediction deep learning screening seasonal feature space derivative
Acceso en línea:	https://ieeexplore.ieee.org/document/11363201/
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