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Journal of the Air & Waste Management Association Volume 55, 2005 - Issue 12
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Technical Paper

Systematic Development of an Artificial Neural Network Model for Real-Time Prediction of Ground-Level Ozone in Edmonton, Alberta, Canada

Diane S. Wirtz Stantec Consulting Ltd., Edmonton, Alberta, Canada
,
Mohamed Gamal El-Din Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, CanadaCorrespondence[email protected]
,
Ahmed G. El-Din HNTB Corporation, Indianapolis, IN, USA
&
Ahmed Idriss Alberta Environment, Air Section, Science and Standards Branch, Edmonton, Alberta, Canada
Pages 1847-1857 | Published online: 01 Mar 2012

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Brian S. Freeman, Graham Taylor, Bahram Gharabaghi & Jesse Thé. (2018) Forecasting air quality time series using deep learning. Journal of the Air & Waste Management Association 68:8, pages 866-886.
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Shamia Hoque, Bakhtier Farouk & Charles N. Haas. (2011) Development of Artificial Neural Network Based Metamodels for Inactivation of Anthrax Spores in Ventilated Spaces Using Computational Fluid Dynamics. Journal of the Air & Waste Management Association 61:9, pages 968-982.
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Articles from other publishers (2)

Gabriel Ibarra-Berastegi, Ana Elias, Astrid Barona, Jon Saenz, Agustin Ezcurra & Javier Diaz de Argandoña. (2008) From diagnosis to prognosis for forecasting air pollution using neural networks: Air pollution monitoring in Bilbao. Environmental Modelling & Software 23:5, pages 622-637.
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M.G. El-Din & W. Moussa. (2005) ANN Modeling of Micro-Machined Gas Sensor Signals. ANN Modeling of Micro-Machined Gas Sensor Signals.

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