Boosting algorithms in energy research: A systematic review

v1v2 (latest)

Boosting algorithms in energy research: A systematic review

1 April 2020

Hristos Tyralis

Georgia Papacharalampous

ArXiv (abs)PDF HTML

Papers citing "Boosting algorithms in energy research: A systematic review"

13 / 13 papers shown

Title
Ensemble learning for blending gridded satellite and gauge-measured precipitation data Georgia Papacharalampous Hristos Tyralis N. Doulamis Anastasios Doulamis 91 8 0 09 Jul 2023
Deep Huber quantile regression networks Hristos Tyralis Georgia Papacharalampous N. Dogulu Kwok-Pan Chun UQCV 141 2 0 17 Jun 2023
Merging satellite and gauge-measured precipitation using LightGBM with an emphasis on extreme quantiles Hristos Tyralis Georgia Papacharalampous N. Doulamis Anastasios Doulamis 70 8 0 02 Feb 2023
A Dynamic Feedforward Control Strategy for Energy-efficient Building System Operation Xia Chen Xiaoye Cai A. Kümpel D. Müller Philipp Geyer AI4CE 34 0 0 23 Jan 2023
Comparison of tree-based ensemble algorithms for merging satellite and earth-observed precipitation data at the daily time scale Georgia Papacharalampous Hristos Tyralis Anastasios Doulamis N. Doulamis 104 11 0 31 Dec 2022
Comparison of machine learning algorithms for merging gridded satellite and earth-observed precipitation data Georgia Papacharalampous Hristos Tyralis Anastasios Doulamis N. Doulamis 68 15 0 17 Dec 2022
A review of predictive uncertainty estimation with machine learning Hristos Tyralis Georgia Papacharalampous UD UQCV 222 47 0 17 Sep 2022
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting Georgia Papacharalampous Hristos Tyralis AI4CE 84 28 0 17 Jun 2022
Time series features for supporting hydrometeorological explorations and predictions in ungauged locations using large datasets Georgia Papacharalampous Hristos Tyralis AI4TS 49 10 0 13 Apr 2022
Hydroclimatic time series features at multiple time scales Georgia Papacharalampous Hristos Tyralis Y. Markonis M. Hanel AI4TS 64 3 0 02 Dec 2021
Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale Georgia Papacharalampous Hristos Tyralis I. Pechlivanidis S. Grimaldi E. Volpi AI4TS 39 12 0 25 Jul 2021
Probabilistic water demand forecasting using quantile regression algorithms Georgia Papacharalampous A. Langousis 42 7 0 16 Apr 2021
Proximal boosting: aggregating weak learners to minimize non-differentiable losses Erwan Fouillen C. Boyer Maxime Sangnier FedML 70 2 0 29 Aug 2018