Prediction of PM10 concentrations in the city of Agadir (Morocco) using non-linear autoregressive artificial neural networks with exogenous inputs (NARX)-Reference-Cited by-同舟云学术

Prediction of PM10 concentrations in the city of Agadir (Morocco) using non-linear autoregressive artificial neural networks with exogenous inputs (NARX)

Published:2021-12 Issue: Volume: Page:
ISSN:2214-7853
Container-title:Materials Today: Proceedings
language:en
Short-container-title:Materials Today: Proceedings

Author:

Adnane Anas,Leghrib Radouane,Chaoufi Jamal,Chirmata Ahmed

Publisher

Elsevier BV

Subject

General Medicine

Reference24 articles.

1. Relationship between particulate matter and childhood astma-basis of a future warning system for central phoenix;Dimitrova;Atmos. Chem. Phys.,2012

2. Long-term ambient fine particulate matter air pollution and lung cancer in a large cohort of never-smokers;Turner;Am. J. Respir. Crit. Care Med.,2011

3. S.K. Friedlander, P. Friedlander, “Smoke, dust and haze: fundamentals of aerosol dynamics”, Topics in Chemical Engineering (2000), Oxford University Press.

4. The influence of meteorology on particulate matter concentrations at an urban Mediterranean location;Galindo;Water Air Soil Pollution,2011

5. Associations of PM2.5 and black carbon concerntrations with traffic, idling, background pollution, and meteorology during school dismissals;Richmond-Bryant;Sci. Total Environ.,2009

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