Results 251 to 260 of about 14,317 (308)

Ensemble Entropy with Adaptive Deep Fusion for Short-Term Power Load Forecasting. [PDF]

Entropy (Basel)
Wang Y, Niu Y, Li X, Dai X, Wang X, Jiang Y, He C, Zhou L.   +7 more
europepmc   +1 more source

CLM-former for enhancing multi-horizon time series forecasting and load prediction in smart microgrids using a robust transformer-based model. [PDF]

Sci Rep
Rahmatinia SM, Hosseini SM, Hosseini-Seno SA.   +2 more
europepmc   +1 more source

Climate Change Reshapes Thermal Suitability for Dairy Cattle in Jiangsu Province (1961-2020). [PDF]

Animals (Basel)
Yang G, Liu F, Zhu G, Liu Q, Wang C, Li D, Guo Z, Zhao H.   +7 more
europepmc   +1 more source

Extended normalised radial basis function for short term load forecasting

, 2004
Kodogiannis, V., Wadge, E.
core  

Short-term forecasting of Indonesia electricity generation using MATLAB based on NARX neural network. [PDF]

PLoS One
Pranata N, Saputri FR.
europepmc   +1 more source

Domain-informed weight forecasting: leveraging behavioral and physiological sequences from wearables. [PDF]

Front Public Health
Cheng L, Wang L, Wang G, Lu B, Wu B, Xiao Y, Huang Q.   +6 more
europepmc   +1 more source

Forecasting Electricity Load Demand: Analysis of the 2001 Rationing Period in Brazil [PDF]

Soares, Lacir Jorge, Souza, Leonardo Rocha   +1 more
core  

Short-term load forecasting based on load profiling

2013 IEEE Power & Energy Society General Meeting, 2013
Load forecasting has gradually becoming a major field of research in electricity industry. Therefore, Load forecasting is extremely important for the electric sector under deregulated environment as it provides a useful support to the power system management. Accurate power load forecasting models are required to the operation and planning of a utility
Ramos, Sérgio, Soares, João, Vale, Zita, Ramos, Sandra   +3 more
openaire   +3 more sources

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An ADMM-LSTM framework for short-term load forecasting

Neural Networks, 2023
Accurate short-term load forecasting (STLF) is crucial for maintaining reliable and efficient operations within power systems. With the continuous increase in volume and variety of energy data provided by renewables, electric vehicles and other sources, long short-term memory (LSTM) has emerged as an attractive approach for STLF due to its ...
Shuo Liu, Zhengmin Kong, Tao Huang 0008, Yang Du 0005, Wei Xiang 0001   +4 more
openaire   +4 more sources