Air quality prediction enhanced by a CNN-LSTM-Attention model optimized with an advanced dung beetle algorithm

Air quality prediction enhanced by a CNN-LSTM-Attention model optimized with an advanced dung beetle algorithm

Air pollution significantly impacts human health and socioeconomic development, making accurate air quality prediction crucial. This study proposes a hybrid CNN-LSTM-Attention model optimized with an improved Dung Beetle Optimization (IDBO) algorithm to enhance predictive performance. IDBO integrat...

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Bibliographic Details
Main Authors: Xiaojie Zhou, Majid Khan Majahar Ali, Farah Aini Abdullah, Lili Wu, Ying Tian, Tao Li, Kaihui Li
Format: Article
Language:English
Published: Nigerian Society of Physical Sciences 2025-08-01
Series:Journal of Nigerian Society of Physical Sciences
Subjects:
Air quality prediction
DBO
CNN
LSTM
Attention
Online Access:https://journal.nsps.org.ng/index.php/jnsps/article/view/2473
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https://journal.nsps.org.ng/index.php/jnsps/article/view/2473

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