Predicting CO<sub>2</sub> Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm

Predicting CO<sub>2</sub> Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm

Global carbon dioxide (CO<sub>2</sub>) emissions are increasing and present substantial environmental sustainability challenges, requiring the development of accurate predictive models. Due to the non-linear and temporal nature of emissions data, traditional machine learning methods—whic...

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Bibliographic Details
Main Authors: Amel Ali Alhussan, Marwa Metwally, S. K. Towfek
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Mathematics
Subjects:
CO<sub>2</sub> emissions
deep learning
optimization algorithms
feature selection
recurrent neural networks
gated recurrent unit (GRU)
Online Access:https://www.mdpi.com/2227-7390/13/9/1481
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