Special Issue "Data Science and Big Data in Energy Forecasting with Applications"
A special issue of Energies (ISSN 1996-1073).
Deadline for manuscript submissions: closed (10 April 2019) | Viewed by 16110
Special Issue Editors

Interests: machine learning; data mining; big data; smart grids
Special Issues, Collections and Topics in MDPI journals

Interests: time series; forecasting; data science and big data
Special Issues, Collections and Topics in MDPI journals

Interests: big data; machine learning; time series; forecasting
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the forecasting of time series, with particular emphasis on energy-related data by means of data science and big data techniques. By energy, we understand any kind of energy, such as electrical, solar, microwave, wind, etc.
Very powerful approaches have been developed in the context of data science and big data analytics during the last years. Such approaches deal with large datasets, considering all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high performance computing or data visualization are now being successfully applied to energy time series forecasting.
We encourage researchers to share their original works in the fields of energy time series forecasting, with a particular emphasis on applications. Topics of primary interest include, but are not limited to:
- Data science and big data in energy time series analysis.
- Data science and big data in energy time series modelling.
- Data science and big data in energy-related time series forecasting.
- Data science and big data in non-parametric time series approaches.
Prof. Dr. José C. Riquelme
Prof. Dr. Alicia Troncoso
Prof. Dr. Francisco Martínez-Álvarez
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- energy
- time series
- forecasting
- data science
- big data