Georgia Papacharalampous

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Investigation of the effect of the hyperparameter optimization and the time lag selection in time series forecasting using machine learning algorithms

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2017 .

Forecasting of geophysical processes using stochastic and machine learning algorithms: Supplementary material

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2017 .

Theoretical and empirical comparison of stochastic and machine learning methods for hydrological processes forecasting

Georgia Papacharalampous, 2016 .

Probabilistic Hydrological Post-Processing at Scale: Why and How to Apply Machine-Learning Quantile Regression Algorithms

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2019, Water.

Large-scale assessment of Prophet for multi-step ahead forecasting of monthly streamflow

Georgia Papacharalampous, Hristos Tyralis, Hristos Tyralis, 2018, Advances in Geosciences.

Comparison between stochastic and machine learning methods for hydrological multi-step ahead forecasting: All forecasts are wrong!

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2017 .

Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity.

Sina Khatami, Elena Volpi, Georgia Papacharalampous, 2020, The Science of the total environment.

Hydrological time series forecasting using simple combinations: Big data testing and investigations on one-year ahead river flow predictability pdf

Georgia Papacharalampous, Hristos Tyralis, Hristos Tyralis, 2020, ArXiv.

Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models

Demetris Koutsoyiannis, Georgia Papacharalampous, Alberto Montanari, 2020 .

Super learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms pdf

Georgia Papacharalampous, Hristos Tyralis, Andreas Langousis, 2019, ArXiv.

Stochastic process-based modelling for hydrological systems

Georgia Papacharalampous, Γεωργία Παπαχαραλάμπους, 2020 .

One-step ahead forecasting of geophysical processes within a purely statistical framework

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2018, Geoscience Letters.

Boosting algorithms in energy research: A systematic review pdf

Georgia Papacharalampous, Hristos Tyralis, 2020, ArXiv.

Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2020 .

Variable Selection in Time Series Forecasting Using Random Forests

Georgia Papacharalampous, Hristos Tyralis, Hristos Tyralis, 2017, Algorithms.

Error Evolution in Multi-Step Ahead Streamflow Forecasting for the Operation of Hydropower Reservoirs

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2017 .

Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2019, Stochastic Environmental Research and Risk Assessment.

Hydrological post-processing using stacked generalization of quantile regression algorithms: Large-scale application over CONUS

Apostolos Burnetas, Georgia Papacharalampous, Hristos Tyralis, 2019, Journal of Hydrology.

Super ensemble learning for daily streamflow forecasting: large-scale demonstration and comparison with multiple machine learning algorithms

Georgia Papacharalampous, Hristos Tyralis, Andreas Langousis, 2020, Neural Computing and Applications.

Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale pdf

Elena Volpi, Georgia Papacharalampous, Hristos Tyralis, 2022, Geoscience Frontiers.

Hydroclimatic time series features at multiple time scales

Georgia Papacharalampous, Yannis Markonis, Martin Hanel, 2021, Journal of Hydrology.

Towards benefitting from diverse inferred features and foreseen behaviours of hydroclimatic variables in predictive modelling contexts

Georgia Papacharalampous, Hristos Tyralis, 2021 .

Streamflow forecasting at large time scales using statistical models

Georgia Papacharalampous, Hristos Tyralis, Andreas Langousis, 2021, Advances in Streamflow Forecasting.

Quantile-Based Hydrological Modelling

Georgia Papacharalampous, Hristos Tyralis, Georgia Papacharalampous, 2021, Water.

Probabilistic Water Demand Forecasting Using Quantile Regression Algorithms pdf

Georgia Papacharalampous, Andreas Langousis, A. Langousis, 2021, Water Resources Research.

Expectile-based hydrological modelling for uncertainty estimation: Life after mean

Sina Khatami, Georgia Papacharalampous, Hristos Tyralis, 2022 .

Boosting algorithms in energy research: A systematic review pdf

Georgia Papacharalampous, Hristos Tyralis, 2021, Neural Comput. Appl..

Explanation and Probabilistic Prediction of Hydrological Signatures with Statistical Boosting Algorithms

Georgia Papacharalampous, Hristos Tyralis, Simon Michael Papalexiou, 2021, Remote. Sens..

How to explain and predict the shape parameter of the generalized extreme value distribution of streamflow extremes using a big dataset

Georgia Papacharalampous, Hristos Tyralis, Hristos Tyralis, 2018, Journal of Hydrology.

Predictability of monthly temperature and precipitation using automatic time series forecasting methods

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2018, Acta Geophysica.

Univariate Time Series Forecasting of Temperature and Precipitation with a Focus on Machine Learning Algorithms: a Multiple-Case Study from Greece

Demetris Koutsoyiannis, Georgia Papacharalampous, Hristos Tyralis, 2018, Water Resources Management.