WSEAS Transactions on Systems


Print ISSN: 1109-2777
E-ISSN: 2224-2678

Volume 18, 2019

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Volume 18, 2019


Automatic Model based on Artificial Neural Networks to Predict the Emissions of Carbon Dioxide (CO2)

AUTHORS: Erik F Méndez, José Herrera, Gabriela Mafla

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ABSTRACT: This research work is based exclusively on the application of artificial neural networks, aimed at predicting the CO2 pollution index. For the design of the ANN, a multilayer network of Backpropagation type has been created and the Levenberg-Marquardt method was used for its training. The neural network consists of three layers: input (Input), hidden (Hidden Layer) and output (Output); the architecture was generated with Matlab software. Good quality results were obtained when the actual values and those predicted by the system were checked, demonstrating that it is a highly accepted model for prediction, favoring the planning processes.

KEYWORDS: carbon dioxide prediction, artificial neural networks, conceptual model, Backpropagation, LevenbergMarquardt method, pollution

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[On line]. Available: https://la.mathworks.com.

WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 18, 2019, Art. #31, pp. 245-252


Copyright Β© 2018 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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