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Energies 2018,11, 213
(a) (b)
(c) (d)
(e) (f)
Figure10.TheforecastingresultsofLSTM:(a)Partial resultsA; (b)Partial resultsB; (c)Partial resultsC;
(d)Partial resultsD; (e)Partial resultsE; (f)Partial resultsF.
(a) (b)
(c) (d)
(e) (f)
Figure11.TheforecastingresultsofproposedDeepEnergy: (a)Partial resultsA; (b)Partial resultsB;
(c)Partial resultsC; (d)Partial resultsD; (e)Partial resultsE; (f)Partial resultsF.
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Short-Term Load Forecasting by Artificial Intelligent Technologies
- Title
- Short-Term Load Forecasting by Artificial Intelligent Technologies
- Authors
- Wei-Chiang Hong
- Ming-Wei Li
- Guo-Feng Fan
- Editor
- MDPI
- Location
- Basel
- Date
- 2019
- Language
- English
- License
- CC BY 4.0
- ISBN
- 978-3-03897-583-0
- Size
- 17.0 x 24.4 cm
- Pages
- 448
- Keywords
- Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
- Category
- Informatik