Multi-Sequence LSTM-RNN Deep Learning and Metaheuristics for Electric Load Forecasting

Single and Multi-Sequence Deep Learning Models for Short and Medium Term Electric Load Forecasting

(2019) Salah Bouktif et al.   Energies

Wind Power Short-Term Prediction Based on LSTM and Discrete Wavelet Transform

(2019) Yao Liu et al.   Applied Sciences-Basel

Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms

(2018) Jesus Lago 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

A comparative study of LSTM neural networks in forecasting day-ahead global horizontal irradiance with satellite data

(2018) Shikhar Srivastava et al.   SOLAR ENERGY

GSP: an automatic programming technique with gravitational search algorithm

(2018) Afsaneh Mahanipour et al.   APPLIED INTELLIGENCE

A review and analysis of regression and machine learning models on commercial building electricity load forecasting

(2017) B. Yildiz et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

(2016) Jui-Sheng Chou et al.   APPLIED ENERGY

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

(2014) Jianzhou Wang et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Decomposition and statistical analysis for regional electricity demand forecasting

(2012) Chi-hsiang Wang et al.   ENERGY

An Empirical Comparison of Machine Learning Models for Time Series Forecasting

(2010) Nesreen K. Ahmed et al.   Econometric Reviews

An artificial neural network (p,d,q) model for timeseries forecasting

(2009) Mehdi Khashei et al.   EXPERT SYSTEMS WITH APPLICATIONS

Time Series Analysis Forecasting and Control

(2009) G. Janacek   JOURNAL OF TIME SERIES ANALYSIS