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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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Predicción de series de datos medioambientales mediante redes complejas

Authors: Enguix, Iván Felis; Navarro, Eduardo Madrid;

Predicción de series de datos medioambientales mediante redes complejas

Abstract

Aplicación de métodos de análisis y predicción de series temporales basados en sistemas dinámicos no lineales y redes complejas. Aplicados a una serie temporal multidimensional obtenida del servicio OpenData de la AEMET, compuesta por diversas variables meteorológicas (temperatura media, mínima, máxima, velocidad media del viento, irradiación solar, y presión atmosférica, entre otras) diarias registradas por la estación de Murcia (código 7178I) desde el 2016-03-01 hasta el 2021-02-01. Estos datos se han recopilado para el proyecto BitBlue: Investigación de técnicas de difusión, procesado y análisis de Big Data del medio marino, financiado por el Instituto de Fomento de la Región de Murcia con el apoyo de los Fondos FEDER.

{"references": ["datos obtenidos de AEMET (OpenData)."]}

Keywords

series temporales multidimensionales, climatología, redes complejas, sistemas dinámicos no lineales

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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