Open access
Sep 2026
Comprehensive Performance Evaluation of Deep Learning Algorithms for Multi-Variable Climate Prediction: RNN, LSTM, and GRU Analysis
Key findings indicate that algorithm choice should be tailored to the prediction target, with temperature variables favoring LSTM, precipitation benefiting from GRU's efficiency, and humidity showing comparable performance across all architectures.
M. M. Akawee, R. Hasan, Munif Ahmed Abdullah et al.
· EDRAAK · 0 citations