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Energies 2018,11, 213
(a) (b)
(c) (d)
(e) (f)
Figure6. The forecasting results of supportvectormachine (SVM): (a) Partial resultsA; (b) Partial
resultsB; (c)Partial resultsC; (d)Partial resultsD; (e)Partial resultsE; (f)Partial resultsF.
(a) (b)
(c) (d)
(e) (f)
Figure 7. The forecasting results of random forest (RF): (a) Partial resultsA; (b) Partial results B;
(c)Partial resultsC; (d)Partial resultsD; (e)Partial resultsE; (f)Partial resultsF.
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Short-Term Load Forecasting by Artificial Intelligent Technologies
- Titel
- Short-Term Load Forecasting by Artificial Intelligent Technologies
- Autoren
- Wei-Chiang Hong
- Ming-Wei Li
- Guo-Feng Fan
- Herausgeber
- MDPI
- Ort
- Basel
- Datum
- 2019
- Sprache
- englisch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-03897-583-0
- Abmessungen
- 17.0 x 24.4 cm
- Seiten
- 448
- Schlagwörter
- Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
- Kategorie
- Informatik