持有資料: 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

The increasing energy demand and expansion of power plants are provoking the effects of greenhouse gas emissions and global warming. To mitigate these issues, renewable energies (like solar, wind, and hydropower) are blessings for modern energy sectors. The study focuses on wind-speed prediction in...

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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.
其他作者:	58831072700
格式:	Article
出版:	Springer Science and Business Media Deutschland GmbH 2024
主題:	NARX neural network Recurrent neural network Renewable energy Time-series forecasting Wind-speed prediction Curve fitting Deep neural networks Errors Gas emissions Global warming Greenhouse gases Mean square error Recurrent neural networks Time series Time series analysis Weather forecasting Wind speed Forecasting: applications Network-based approach Neural network model Performance Prediction modelling Renewable energies Time series forecasting Wind speed prediction Wind time series Neural network models
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A comprehensive study and performance analysis of deep neural network-based approaches in wind time-series forecasting

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