A comprehensive study and performance analysis of deep neural network-based approaches in wind time-series forecasting

A comprehensive study and performance analysis of deep neural network-based approaches in wind time-series forecasting

Curve fitting; Deep neural networks; Errors; Forecasting; Gas emissions; Gas plants; Global warming; Graphic methods; Mean square error; Recurrent neural networks; Time series; Time series analysis; Wind; Forecasting: applications; NARX neural network; Network-based approach; Neural network model; P...

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Bibliographic Details
Main Authors: Rahman M.M., Shakeri M., Khatun F., Tiong S.K., Alkahtani A.A., Samsudin N.A., Amin N., Pasupuleti J., Hasan M.K.
Other Authors: 57207730841
Format: Article
Published: Springer Science and Business Media Deutschland GmbH 2023
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Institution: Universiti Tenaga Nasional
Description
Summary:Curve fitting; Deep neural networks; Errors; Forecasting; Gas emissions; Gas plants; Global warming; Graphic methods; Mean square error; Recurrent neural networks; Time series; Time series analysis; Wind; Forecasting: applications; NARX neural network; Network-based approach; Neural network model; Performance; Prediction modelling; Renewable energies; Time series forecasting; Wind speed prediction; Wind time series; Greenhouse gases

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