crossrefWater2025-09-10Cited by 6
Deep Signals: Enhancing Bottom Temperature Predictions in Norway’s Mjøsa Lake Through VMD- and EMD-Boosted Machine Learning Models
Sertac Oruc, Mehmet Ali Hınıs, Zeliha Selek, Türker Tuğrul
In this study, we benchmark various machine learning techniques against a synthetic but physically based reference time series (model-simulated (ERA5-Land/FLake) bottom-temperature series) and assess whether decomposition methods (VMD and EMD) improve forecast accuracy using Supp…