Long Term Household Electricity Demand Forecasting Based on RNN-GBRT Model and a Novel Energy Theft Detection Method
The long-term electricity demand forecast of the consumer utilization is essential for the energy provider to analyze the future demand and for the accurate management of demand response. Forecasting the consumer electricity demand with efficient and accurate strategies will help the energy provider...
Auteurs principaux: | Santanu Kumar Dash, Michele Roccotelli, Rasmi Ranjan Khansama, Maria Pia Fanti, Agostino Marcello Mangini |
---|---|
Format: | Article |
Langue: | English |
Publié: |
MDPI AG
2021-09-01
|
Collection: | Applied Sciences |
Sujets: | |
Accès en ligne: | https://www.mdpi.com/2076-3417/11/18/8612 |
Documents similaires
-
The truth about identity theft /
par: 328730 Stickley, Jim
Publié: (2009) -
Identity theft handbook : detection, prevention, and security /
par: 350516 Biegelman, Martin T.
Publié: (2009) -
Cycle theft /
par: 250612 Morgan, J. M., et autres
Publié: (1984) -
Identity theft /
par: Stewart, Gail B. (Gail Barbara), 1949-
Publié: (2007) -
RNN-BiLSTM-CRF based amalgamated deep learning model for electricity theft detection to secure smart grids
par: Aqsa Khalid, et autres
Publié: (2024-02-01)