Solar Irradiation Prediction Hybrid Framework Using Regularized Convolutional BiLSTM-Based Autoencoder Approach

Solar irradiance prediction is an essential subject in renewable energy generation. Prediction enhances the planning and management of solar installations and provides several economic benefits to energy companies. Solar irradiation, being highly volatile and unpredictable makes the forecasting task...

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Vydáno v:	IEEE access Ročník 11; s. 131362 - 131375
Hlavní autoři:	Chiranjeevi, Madderla, Karlamangal, Skandha, Moger, Tukaram, Jena, Debashisha
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Artificial neural networks Autoencoder Autoregressive processes Benchmarks BiLSTM convolution neural network Convolutional neural networks Decoding Encoding Forecasting Irradiance Irradiation Long short term memory Mathematical models Model accuracy Performance measurement Predictive models Radiation effects Representations Solar power generation Solar radiation Space exploration
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
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