Improving Monthly Precipitation Forecasting with GRU-LSTM Model in Turkey

forecasts due to the country's susceptibility to extreme weather events
like heavy precipitation, flash floods, and typhoons. On the other
hand, Predictions enable officials to implement preventive actions
and alert the community. Hence, researching forecasting precipitation
in Turkey is essential.This research uses two combined deep learning
hybrid models of Convolutional Neural Network, Long Short-Term
Memory (CNN-LSTM), and Gated Recurrent Units-Long ShortTerm Memory (GRU-LSTM) to predict the monthly precipitation of
Istanbul and Konya between 2000 to 2023. From the research results,
it can be concluded that the GRU-LSTM model is generally better
than the CNN-LSTM model in monthly forecasting.