Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/101673
Title: Prediction the dynamic of changes in the concentrations of main greenhouse gases by an artificial neural network type NARX
Authors: Sergeev, A.
Buevich, A.
Shichkin, A.
Baglaeva, E.
Subbotina, I.
Medvedev, A.
Sergeeva, M.
Issue Date: 2020
Publisher: American Institute of Physics Inc.
Citation: Prediction the dynamic of changes in the concentrations of main greenhouse gases by an artificial neural network type NARX / A. Sergeev, A. Buevich, A. Shichkin, et al. — DOI 10.1063/5.0027183 // AIP Conference Proceedings. — 2020. — Vol. 2293. — 120020.
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.
URI: http://hdl.handle.net/10995/101673
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85097977145
PURE ID: 20396488
ed987641-704e-46f1-9515-4f34b5be571c
ISSN: 0094243X
ISBN: 9780735440258
DOI: 10.1063/5.0027183
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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