Deep learning for load forecasting with smart meter data: Online Adaptive Recurrent Neural Network

Spatial autocorrelation and entropy for renewable energy forecasting

(2019) Michelangelo Ceci et al.   DATA MINING AND KNOWLEDGE DISCOVERY

Short-Term Electricity Load Forecasting Model Based on EMD-GRU with Feature Selection

(2019) Xin Gao et al.   Energies

Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network

(2019) Shuang Han et al.   APPLIED ENERGY

Data Stream Mining Applied to Maximum Wind Forecasting in the Canary Islands

(2019) Javier J. Sánchez-Medina et al.   SENSORS

Robust ensemble learning framework for day-ahead forecasting of household based energy consumption

(2018) Mohammad H. Alobaidi et al.   APPLIED ENERGY

Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †

(2018) Salah Bouktif et al.   Energies

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

(2018) Yi Wang et al.   IEEE Transactions on Smart Grid

Robust functional regression for wind speed forecasting based on Sparse Bayesian learning

(2018) Yun Wang et al.   RENEWABLE ENERGY

Assessment of deep recurrent neural network-based strategies for short-term building energy predictions

(2018) Cheng Fan et al.   APPLIED ENERGY

LSTM: A Search Space Odyssey

(2017) Klaus Greff et al.   IEEE Transactions on Neural Networks and Learning Systems

On evaluating stream learning algorithms

(2012) João Gama et al.   MACHINE LEARNING