Enhancing PM<sub>2.5</sub> Air Pollution Prediction Performance by Optimizing the Echo State Network (ESN) Deep Learning Model Using New Metaheuristic Algorithms

Enhancing PM<sub>2.5</sub> Air Pollution Prediction Performance by Optimizing the Echo State Network (ESN) Deep Learning Model Using New Metaheuristic Algorithms

Air pollution presents significant risks to both human health and the environment. This study uses air pollution and meteorological data to develop an effective deep learning model for hourly PM<sub>2.5</sub> concentration predictions in Tehran, Iran. This study evaluates efficient metah...

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Bibliographic Details
Main Authors: Iman Zandi, Ali Jafari, Aynaz Lotfata
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Urban Science
Subjects:
Boruta-XGBoost
Echo State Network deep learning model
metaheuristic algorithms
PM<sub>2.5</sub> air pollution concentration prediction
wavelet transform
Online Access:https://www.mdpi.com/2413-8851/9/5/138
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