On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models
Air pollution, particularly fine (PM<sub>2.5</sub>) and coarse (PM<sub>10</sub>) particulate matter, poses significant risks to public health and environmental sustainability. This study aims to develop robust predictive and forecasting models for hourly PM concentrations in...
Saved in:
| Main Authors: | Youness El Mghouchi, Mihaela Tinca Udristioiu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/15/8254 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Optimizing Air Pollution Forecasting Across Temporal Scales: A Case Study in Salamanca, Mexico
by: Francisco-Javier Moreno-Vazquez, et al.
Published: (2025-02-01) -
Deep learning framework for hourly air pollutants forecasting using encoding cyclical features across multiple monitoring sites in Beijing
by: Abdel Salam Alsabagh, et al.
Published: (2025-07-01) -
One Axis, Two Faces: The Shared Biology of PMS and Migraine
by: Michalina Makieła, et al.
Published: (2025-05-01) -
AirTrace-SA: Air Pollution Tracing for Source Attribution
by: Wenchuan Zhao, et al.
Published: (2025-07-01) -
CHEMICAL AND BIOLOGICAL AIR POLLUTANTS, AS PARAMETERS OF COMPLEX AIR QUALITY INDICES
by: TEKLA EÖTVÖS, et al.
Published: (2007-12-01)