On Ioannina ERA5 hourly data, hybrid 1D-CNN–RNN models raise a composite WQS by 1.22–1.63% at 24 h and 0.44–0.45% at 168 h over the best single-layer GRU/LSTM baselines.
A deep learning based framework for enhanced reference evapotranspiration estimation: Evaluating accuracy and forecasting strategies,
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Exploratory Analysis of Deep Learning Models for Forecasting Meteorological Parameters in the Agricultural Sector
On Ioannina ERA5 hourly data, hybrid 1D-CNN–RNN models raise a composite WQS by 1.22–1.63% at 24 h and 0.44–0.45% at 168 h over the best single-layer GRU/LSTM baselines.