A comprehensive evaluation of ai techniques for air quality index prediction: RNNs and transformers

A comprehensive evaluation of ai techniques for air quality index prediction: RNNs and transformers

This study evaluates the effectiveness of Recurrent Neural Networks (RNNs) and Transformer-based models in predicting the Air Quality Index (AQI). Accurate AQI prediction is critical for mitigating the significant health impacts of air pollution and plays a vital role in public health protection an...

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Bibliographic Details
Main Authors: Pablo Andrés Buestán Andrade, Pedro Esteban Carrión Zamora, Anthony Eduardo Chamba Lara, Juan Pablo Pazmiño Piedra
Format: Article
Language:English
Published: Universidad Politécnica Salesiana 2025-01-01
Series:Ingenius: Revista de Ciencia y Tecnología
Subjects:
Air Quality Index
RNN
LSTM
Transformers
Pollution Forecasting
Online Access:https://revistas.ups.edu.ec/index.php/ingenius/article/view/9557
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