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Short term net load forecasting using computational intelli..:

, In: 7th E-Mobility Power System Integration Symposium (EMOB 2023),

Laouali, I. H. ; Italiano, N. ; Casaleiro, Â... - p. None , 2023

Link: https://doi.org/10.1049/icp.2023.2696

RT 
T1 <cTitle>7th E-Mobility Power System Integration Symposium (EMOB 2023)</cTitle>: T1 <Title>Short term net load forecasting using computational intelligence techniques</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10324493&Exemplar=1&LAN=DE
				
A1 Laouali, I. H.
A1 Italiano, N.
A1 Casaleiro, Â.
A1 Alvite, I.
A1 da Silva, N. P.
YR 2023
K1 decision trees
K1 distributed power generation
K1 learning (artificial intelligence)
K1 load forecasting
K1 power engineering computing
K1 power grids
K1 power system reliability
K1 random forests
K1 recurrent neural nets
K1 regression analysis
K1 support vector machines
K1 computational intelligence techniques
K1 electricity grid
K1 extreme gradient boosting algorithm
K1 incremental learning
K1 long short-term memory
K1 Portugal
K1 recurrent neural network
K1 short term net load forecasting
K1 system reliability
K1 system stability
K1 TSO-DSO interface
SP None
LK http://dx.doi.org/https://doi.org/10.1049/icp.2023.2696
DO https://doi.org/10.1049/icp.2023.2696
SF ELIB - SuUB Bremen

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