Papers › Localized Weather Prediction Using Kolmogorov-Arnold Network-Based Models and Deep RNNs
Localized Weather Prediction Using Kolmogorov-Arnold Network-Based Models and Deep RNNs
Ange-Clement Akazan, Verlon Roel Mbingui, Gnankan Landry Regis N'guessan, Issa Karambal
Weather forecasting is crucial for managing risks and economic planning, particularly in tropical Africa, where extreme events severely impact livelihoods. Yet, existing forecasting methods often struggle with the region's complex, non-linear weather patterns. This study benchmarks deep recurrent neural networks such as LSTM, GRU, BiLSTM, BiGRU, and Kolmogorov-Arnold-based models (KAN and TKAN) for daily forecasting of temperature, precipitation, and pressure in two tropical cities: Abidjan, Cote d'Ivoire (Ivory Coast) and Kigali (Rwanda). We further introduce two customized variants of TKAN that replace its original SiLU activation function with GeLU and \texttt{MiSH}, respectively. Using station-level meteorological data spanning from 2010 to 2024, we evaluate all the models on standard regression metrics. KAN achieves temperature prediction (R²=0.9986 in Abidjan, $0.9998$ in Kigali, MSE < 0.0014 ° C ²), while TKAN variants minimize absolute errors for precipitation forecasting in low-rainfall regimes. The customized TKAN models demonstrate improvements over the standard TKAN across both datasets. Classical \texttt{RNNs} remain highly competitive for atmospheric pressure (R² ≈0.83-0.86), outperforming KAN-based models in this task. These results highlight the potential of spline-based neural architectures for efficient and data-efficient forecasting.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections