Hybrid deep learning model for ozone concentration prediction: comprehensive evaluation and comparison with various machine and deep learning algorithms

Hybrid deep learning model for ozone concentration prediction: comprehensive evaluation and comparison with various machine and deep learning algorithms

To accurately predict tropospheric ozone concentration(O3), it is needed to investigate the variety of artificial intelligence techniques’ performance, such as machine learning, deep learning and hybrid models. This research aims to effectively predict the hourly ozone trend via fewer input variable...

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Bibliographic Details
Main Authors: Ayman Yafouz, Ali Najah Ahmed, Nur’atiah Zaini, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
air quality
ozone concentration prediction
machine learning
deep learning
hybrid model
uncertainty and sensitivity analysis
Online Access:http://dx.doi.org/10.1080/19942060.2021.1926328

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