Publicación:
Forecasting of Meteorological Weather Time Series Through a Feature Vector Based on Correlation

dc.contributor.author Ramos M.M.P. es_PE
dc.contributor.author Del Alamo C.L. es_PE
dc.contributor.author Zapana R.A. es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2019
dc.description.abstract Nowadays, the impacts of climate change are harming many countries around the world. For this reason, the scientific community is interested in improving methods to forecast weather events, so it is possible to avoid people from being injured. One important thing in the development of time series forecasting methods is to consider the set of values over time that facilitates the prediction of future value. In this sense, we propose a new feature vector based on the correlation and autocorrelation functions. These measures reflect how the observations of a time series are related to each other. Then, univariate forecasting is performed using Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) deep neural network. Finally, we compared the new model with linear and non-linear models. Reported results exhibit that MLP and LSTM models using the proposed feature vector, they show promising results for univariate forecasting. We tested our method on a real-world dataset from the Fisher weather station (Harvard Forest). © 2019, Springer Nature Switzerland AG.
dc.description.sponsorship Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec
dc.identifier.doi https://doi.org/10.1007/978-3-030-29888-3_44
dc.identifier.scopus 2-s2.0-85072859647
dc.identifier.uri https://hdl.handle.net/20.500.12390/2731
dc.language.iso eng
dc.publisher Springer Verlag
dc.relation.ispartof Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rights info:eu-repo/semantics/openAccess
dc.subject Weather forecast
dc.subject Correlation es_PE
dc.subject Deep Learning es_PE
dc.subject Feature vector es_PE
dc.subject Forecasting of time series es_PE
dc.subject Non-linear forecast models es_PE
dc.subject.ocde http://purl.org/pe-repo/ocde/ford#1.05.10
dc.title Forecasting of Meteorological Weather Time Series Through a Feature Vector Based on Correlation
dc.type info:eu-repo/semantics/article
dspace.entity.type Publication
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