Artículo
Data Science and Big Data in Energy Forecasting
Autor/es | Martínez Álvarez, Francisco
Troncoso Lora, Alicia Riquelme Santos, José Cristóbal ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2018-11 |
Fecha de depósito | 2019-02-20 |
Publicado en |
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Resumen | This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, which was published at MDPI’s Energies journal. The special issue took place in 2017 and accepted a ... This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, which was published at MDPI’s Energies journal. The special issue took place in 2017 and accepted a total of 13 papers from 7 different countries. Electrical, solar and wind energy forecasting were the most analyzed topics, introducing new methods with applications of utmost relevance. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España Ministerio de Economía. España |
Identificador del proyecto | TIN2014-55894-C2-R
![]() TIN2017-88209-C2-R ![]() |
Cita | Martínez Álvarez, F., Troncoso Lora, A. y Riquelme Santos, J.C. (2018). Data Science and Big Data in Energy Forecasting. Energies, 11 (11 - 3224) |
Ficheros | Tamaño | Formato | Ver | Descripción |
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energies-11-03224 (1).pdf | 147.0Kb | ![]() | Ver/ | |