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AIP Conference ProceedingsVolume 2293, 24 November 2020, Article number 120020International Conference on Numerical Analysis and Applied Mathematics 2019, ICNAAM 2019; Sheraton Rhodes ResortRhodes; Greece; 23 September 2019 through 28 September 2019; Code 165330

Prediction the dynamic of changes in the concentrations of main greenhouse gases by an artificial neural network type NARX(Conference Paper)(Open Access)

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  • aUral Federal University, Mira str., 19, Ekaterinburg, 620002, Russian Federation
  • bInstitute of Industrial Ecology, UB, RAS, S. Kovalevskoy str., 20, Ekaterinburg, 620990, Russian Federation

Abstract

The paper considered the use of one of the most accurate artificial neural networks for predicting time series - a nonlinear autoregressive neural network with external input (NARX) for predicting the dynamics of changes in the concentrations of the main greenhouse gases. The data were obtained in the course of monitoring the dynamics of changes in the main greenhouse gases on the Arctic island Belyy, Russia. The data of the surface concentration of methane, carbon dioxide, carbon monoxide and water vapor were used. A time interval of 168 hours was chosen for the study during the summer period (July-August 2016). The NARX model accurately predicted concentration changes for all greenhouse gases. © 2020 American Institute of Physics Inc.. All rights reserved.

  • ISSN: 0094243X
  • ISBN: 978-073544025-8
  • Source Type: Conference Proceeding
  • Original language: English
  • DOI: 10.1063/5.0027183
  • Document Type: Conference Paper
  • Volume Editors: Simos T.E.,Simos T.E.,Simos T.E.,Simos T.E.,Simos T.E.,Tsitouras C.
  • Publisher: American Institute of Physics Inc.

  Medvedev, A.; Ural Federal University, Mira str., 19, Ekaterinburg, Russian Federation;
© Copyright 2020 Elsevier B.V., All rights reserved.

Cited by 4 documents

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