Accurate and efficient forecasted wind energy using selected temporal metrological variables and wind direction
The aim of this work is to find the most efficient and suitable input features to be selected for forecasting monthly wind energy accurately. Machine learning is employed for a modular pipelined neural network, composed of time-delayed and feedforward networks with features of metrological variables...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Energy Conversion and Management: X |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S259017452200109X |