Comparative Investigation of Machine Learning and Deep Learning Approaches for Air Quality Prediction
Air pollution is a critical environmental issue with significant impacts on human health and ecosystems, exacerbated by urbanization and industrialization, leading to increased emissions. Forecasting air quality accurately is crucial for risk mitigation and policy direction. Recent advancements in d...
Saved in:
| Main Author: | Zhang Borui |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
|
| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/04/itmconf_iwadi2024_02002.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Air Quality Prediction in Beijing: Machine and Deep Learning Analysis
by: Das Shuvendu, et al.
Published: (2024-01-01) -
Indoor Air Quality Prediction in Sick Building Using Machine and Deep Learning: Comparative Analysis
by: Hayder Qasim Flayyih, et al.
Published: (2025-03-01) -
Prediction of particulate matter PM2.5 level in the air of Islamabad, Pakistan by using machine learning and deep learning approaches
by: Muhammad Waqas, et al.
Published: (2025-03-01) -
Predicting spread through air space of lung adenocarcinoma based on deep learning and machine learning models
by: Zengming Wang, et al.
Published: (2025-08-01) -
Analysis and Prediction for Air Quality Using Various Machine Learning Models
by: To-Hieu Dao, et al.
Published: (2022-02-01)