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Cited article:

Power grid investment forecasting method based on PSO‐GRU neural network

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Concurrency and Computation: Practice and Experience 35 (27) (2023)
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International Journal of Energy and Environmental Engineering 14 (3) 497 (2023)
https://doi.org/10.1007/s40095-022-00530-4

Solar Energy Production Forecasting Based on a Hybrid CNN-LSTM-Transformer Model

Elham M. Al-Ali, Yassine Hajji, Yahia Said, et al.
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Accurate photovoltaic power prediction models based on deep convolutional neural networks and gated recurrent units

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Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 44 (3) 6303 (2022)
https://doi.org/10.1080/15567036.2022.2097751

Solar Irradiance Forecasting to Short-Term PV Power: Accuracy Comparison of ANN and LSTM Models

Victor Hugo Wentz, Joylan Nunes Maciel, Jorge Javier Gimenez Ledesma and Oswaldo Hideo Ando Junior
Energies 15 (7) 2457 (2022)
https://doi.org/10.3390/en15072457

Deep Learning Algorithms to Predict Output Electrical Power of an Industrial Steam Turbine

Kossai Fakir, Chouaib Ennawaoui and Mahmoud El Mouden
Applied System Innovation 5 (6) 123 (2022)
https://doi.org/10.3390/asi5060123