Long-Term Hourly Ozone Forecasting via Time–Frequency Analysis of ICEEMDAN-Decomposed Components: A 36-Hour Forecast for a Site in Beijing
Surface ozone is a pollutant linked to higher risks of cardiopulmonary diseases with long-term exposure. Timely forecasting of ozone levels helps authorities implement preventive measures to protect public health and safety. However, few studies have been able to reliably provide long-term hourly oz...
Saved in:
Main Authors: | Taotao Lv, Yulu Yi, Zhuowen Zheng, Jie Yang, Siwei Li |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/17/14/2530 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing agricultural sustainability: Time series forecasting with ICEEMDAN-VMD-GRU for economic-resilience
by: Aastha M. Sathe, et al.
Published: (2025-09-01) -
Advanced Multivariate Models Incorporating Non-Climatic Exogenous Variables for Very Short-Term Photovoltaic Power Forecasting
by: Isidro Fraga-Hurtado, et al.
Published: (2025-06-01) -
Construction of time series prediction and dynamic evaluation model for environmental factors in pregnant sow houses in winter
by: Xuehan Li, et al.
Published: (2025-12-01) -
Music audio emotion regression using the fusion of convolutional neural networks and bidirectional long short-term memory models
by: Yi Qiu, et al.
Published: (2025-07-01) -
A Novel Audio-Perception-Based Algorithm for Physiological Monitoring
by: Zixuan Zhang, et al.
Published: (2025-06-01)