Data Science and Big Data in Energy Forecasting

Francisco Martínez-Álvarez, Alicia Troncoso and José C. Riquelme
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Francisco Martínez-Álvarez: Data Science and Big Data Lab, Pablo de Olavide University, ES-41013 Seville, Spain
Alicia Troncoso: Data Science and Big Data Lab, Pablo de Olavide University, ES-41013 Seville, Spain
José C. Riquelme: Department of Computer Science, University of Seville, ES-41012 Seville, Spain

Energies, 2018, vol. 11, issue 11, 1-2

Abstract: 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.

Keywords: energy; time series; forecasting; data mining; big data (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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