Deep Learning and Time Series for the Prediction of Monthly Precipitation. A Case Study in the Department of Boyacá, Colombia

Deep Learning and Time Series for the Prediction of Monthly Precipitation. A Case Study in the Department of Boyacá, Colombia

Context: This paper proposes a method for the prediction of monthly precipitation in the department of Boyacá using models based on deep neural networks (DNNs). These approaches have achieved significant improvements in prediction accuracy when compared to traditional methods. Method: Data with a s...

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Bibliographic Details
Main Authors: Yesid Esteban Duarte, Marco Javier Suárez Barón, Oscar Javier García Cabrejo, César Augusto Jaramillo Acevedo, Carlos Augusto Meneses Escobar
Format: Article
Language:Spanish
Published: Universidad Distrital Francisco José de Caldas 2025-03-01
Series:Ingeniería
Subjects:
deep learning
neural networks
lstm
convlstm
time series
Online Access:https://revistas.udistrital.edu.co/index.php/reving/article/view/21930
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https://revistas.udistrital.edu.co/index.php/reving/article/view/21930

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