Litcius/Paper detail

Bi-LSTM-Based Deep Stacked Sequence-to-Sequence Autoencoder for Forecasting Solar Irradiation and Wind Speed

Neelam Mughees, Mujtaba Hussain Jaffery, Abdullah Mughees, Anam Mughees, Krzysztof Ejsmont

2023Computers, materials & continua/Computers, materials & continua (Print)15 citationsDOIOpen Access PDF

Abstract

Wind and solar energy are two popular forms of renewable energy used in microgrids and facilitating the transition towards net-zero carbon emissions by 2050. However, they are exceedingly unpredictable since they rely highly ... | Find, read and cite all the research you need on Tech Science Press

Topics & Concepts

AutoencoderDeep learningComputer scienceArtificial intelligenceSequence (biology)Renewable energyMATLABWind speedArtificial neural networkEngineeringMeteorologyElectrical engineeringBiologyGeneticsPhysicsOperating systemEnergy Load and Power ForecastingSolar Radiation and PhotovoltaicsWind Energy Research and Development
Bi-LSTM-Based Deep Stacked Sequence-to-Sequence Autoencoder for Forecasting Solar Irradiation and Wind Speed | Litcius