Geographically Aware Air Quality Prediction Through CNN-LSTM-KAN Hybrid Modeling with Climatic and Topographic Differentiation

Geographically Aware Air Quality Prediction Through CNN-LSTM-KAN Hybrid Modeling with Climatic and Topographic Differentiation

Air pollution poses a pressing global challenge, particularly in rapidly industrializing nations like China where deteriorating air quality critically endangers public health and sustainable development. To address the heterogeneous patterns of air pollution across diverse geographical and climatic...

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Bibliographic Details
Main Authors: Yue Hu, Yitong Ding, Wenjing Jiang
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Atmosphere
Subjects:
air quality index (AQI) prediction
deep learning hybrid model learning
Gaussian filtering
correlation analysis
Online Access:https://www.mdpi.com/2073-4433/16/5/513
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