Development and application of a hybrid artificial neural network model for simulating future stream flows in catchments with limited in situ observed data
The need to develop new and computationally efficient artificial intelligence models that accurately simulate river flows in data-scarce regions, considering not only current but also projected future climate change conditions is vital. In this study, a hybrid artificial neural network (ANN) model that combines HEC-HMS and the feed-forward neural network (FFNN) was developed in the Python programm
