150 citations · 218 across the 4 of their papers we have counts for
4 papers
Probabilistic water demand forecasting using quantile regression algorithms
Georgia Papacharalampous, Andreas Langousis
Machine and statistical learning algorithms can be reliably automated and applied at scale. Therefore, they can constitute a considerable asset for designing practical forecasting…
Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity
Georgia Papacharalampous, Hristos Tyralis, Simon Michael Papalexiou +4
Hydroclimatic time series analysis focuses on a few feature types (e.g., autocorrelations, trends, extremes), which describe a small portion of the entire information content of th…
ITSO: A novel Inverse Transform Sampling-based Optimization algorithm for stochastic search
Nikolaos P. Bakas, Vagelis Plevris, Andreas Langousis +1
Optimization algorithms appear in the core calculations of numerous Artificial Intelligence (AI) and Machine Learning methods, as well as Engineering and Business applications. Fol…
Super ensemble learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms
Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis
Daily streamflow forecasting through data-driven approaches is traditionally performed using a single machine learning algorithm. Existing applications are mostly restricted to exa…