A Machine Learning Approach to Predict Air Quality in California
Predicting air quality is a complex task due to the dynamic nature, volatility, and high variability in time and space of pollutants and particulates. At the same time, being able to model, predict, and monitor air quality is becoming more and more relevant, especially in urban areas, due to the obs...
Saved in:
Main Authors: | Mauro Castelli, Fabiana Martins Clemente, Aleš Popovič, Sara Silva, Leonardo Vanneschi |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/8049504 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Machine Learning Approach for Environmental Assessment on Air Quality and Mitigation Strategy
by: Chetan Shetty, et al.
Published: (2024-01-01) -
Machine learning algorithms in air quality modeling
by: A. Masih
Published: (2019-10-01) -
Interpretable Machine Learning Approaches for Forecasting and Predicting Air Pollution: A Systematic Review
by: Anass Houdou, et al.
Published: (2023-11-01) -
Enhanced Forecasting and Assessment of Urban Air Quality by an Automated Machine Learning System: The AI‐Air
by: Jiayu Yang, et al.
Published: (2025-01-01) -
Machine learning approach to student performance prediction of online learning.
by: Jing Wang, et al.
Published: (2025-01-01)