State of the Art of Machine Learning Models in Energy Systems, a Systematic Review
Amir Hosein Mosavi, Mohsen Salimi, Sina Ardabili, Timon Rabczuk, Shahaboddin Shamshirband, Annamária R. Várkonyi-Kóczy
Journal
- ISSN / E-ISSN
- — / —
- DOI
- 10.3390/en12071301 ↗
- Volume · Issue · Pages
- 12 · 7 · 1301-1301
- Publisher
- Multidisciplinary Digital Publishing Institute (MDPI)
- Article URL
- http://dx.doi.org/10.3390/en12071301 ↗
- Article details
- Unverified
Publication date (each date has its type and source)
04 Apr 2019
OpenAlex publication date · source: OpenAlex
| Type | Date | Source |
|---|---|---|
| OpenAlex publication date | 04 Apr 2019 | OpenAlex |
Keywords (as given): machine learning models; energy systems; hybrid machine learning; model taxonomy; load forecasting; renewable energy forecasting; solar energy; wind energy; biofuels; energy efficiency; energy governance; model evaluation
HEC Status at Publication Not the journal's current status
HEC Status at PublicationNot conclusive
Historical status could not be conclusively determined.
- HEC status cannot be determined for this date: no HEC list is recorded as in effect on it.
Best available information, not a definitive status: HEC status cannot be determined for this date: no HEC list is recorded as in effect on it.
- Journal
- Energies
- Publication date used
- 04 Apr 2019 (OpenAlex publication date)
- Applicable HEC period
- None recorded for this date
- Category
- —
- Recognition status
- Unknown (NO_PERIOD_FOR_DATE)
- Source
- —
- Verification status
- Not available
This is an automatically generated summary based on the information available on the publication date. Terms & conditions apply.