Holdings: Prediction of atmospheric carbon monoxide concentration utilizing different machine learning algorithms: A case study in Kuala Lumpur, Malaysia

Prediction of atmospheric carbon monoxide concentration utilizing different machine learning algorithms: A case study in Kuala Lumpur, Malaysia

Insidious toxin carbon monoxide (CO) can imitate a wide range of different disease states. Clinicians have, and will continue to have, serious concerns about the impact of CO imbalances on the human body. Carbon monoxide concentration has been exceeding the allowable levels in Malaysia. Owing to thi...

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Bibliographic Details
Main Authors:	Latif S.D., Almalayih M., Yafouz A., Ahmed A.N., Zaini N., Irwan D., AlDahoul N., Sherif M., El-Shafie A.
Other Authors:	57216081524
Format:	Article
Published:	Elsevier B.V. 2024
Subjects:	Air Quality Carbon monoxide concentration Machine learning Predictive model Uncertainty analysis Air quality Atmospheric humidity Decision trees Forecasting Learning algorithms Learning systems Multilayer neural networks Nitric oxide Nitrogen oxides Quality control Sulfur dioxide Support vector machines Wind Atmospheric carbon monoxide Machine learning algorithms Machine learning techniques Machine-learning Malaysia Multilayers perceptrons Neural-networks Performance Predictive models Carbon monoxide
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Prediction of atmospheric carbon monoxide concentration utilizing different machine learning algorithms: A case study in Kuala Lumpur, Malaysia

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