Hristos Tyralis 个人学术档案

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Georgia PapacharalampousNational Technical University of Athens在 hydro.ntua.gr 的电子邮件经过验证
Demetris KoutsoyiannisProf. Em., Hydrology & Hydrosystems; Dept. Water Resources; School of Civil Engineering; NTU Athens在 itia.ntua.gr 的电子邮件经过验证
Andreas LangousisProfessor of Hydrology and Hydraulics, Department of Civil Engineering, University of Patras, Greece在 upatras.gr 的电子邮件经过验证
Nikos MamassisProfessor of Hydrology; Dept. of Water Resources; School of Civil Engineering; NTU Athens在 itia.ntua.gr 的电子邮件经过验证
Panayiotis DimitriadisDepartment of Water Resources and Environmental Engineering, School of Civil Engineering, NTUA在 itia.ntua.gr 的电子邮件经过验证
Theano IliopoulouNational Technical University of Athens, School of Civil Engineering, Department of Water Resources在 central.ntua.gr 的电子邮件经过验证
Nikolaos DoulamisNational Technical University of Athens在 cs.ntua.gr 的电子邮件经过验证
Anastasios DoulamisNational Technical University of Athens在 cs.ntua.gr 的电子邮件经过验证
Alberto MontanariProfessor of Hydrology and Water Engineering, University of Bologna在 unibo.it 的电子邮件经过验证
Georgios KarakatsanisPhD Researcher in Energy, environment and economic growth, National Technical University of Athens在 itia.ntua.gr 的电子邮件经过验证
Simon Michael PapalexiouAssociate Professor, University of Calgary, Canada在 ucalgary.ca 的电子邮件经过验证
Apostolos BurnetasDepartment of Mathematics, National and Kapodistrian University of Athens在 math.uoa.gr 的电子邮件经过验证
Bellie SivakumarIndian Institute of Technology Bombay在 iitb.ac.in 的电子邮件经过验证
Aristoteles TegosNational Technical University Athens在 itia.ntua.gr 的电子邮件经过验证
Elena VolpiUniversità Roma Tre在 uniroma3.it 的电子邮件经过验证
Salvatore GRIMALDIProfessor of Hydrology, Università degli Studi della Tuscia, Viterbo, Italy在 unitus.it 的电子邮件经过验证
Sina KhatamiUniversity of Melbourne在 unimelb.edu.au 的电子邮件经过验证
Yorgos N. PhotisProfessor of Geographical Analysis and Locational Planning, National Technical University of Athens在 mail.ntua.gr 的电子邮件经过验证
Yannis MarkonisCzech University of Life Sciences Prague在 fzp.czu.cz 的电子邮件经过验证
Andreas EfstratiadisAssistant Professor, National Technical University of Athens在 itia.ntua.gr 的电子邮件经过验证

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Hristos Tyralis

Hellenic Air Force

在 hydro.ntua.gr 的电子邮件经过验证 - 首页

hydrology probabilistic forecasting random forests machine learning statistical learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Twenty-three Unsolved Problems in Hydrology (UPH)–a community perspective G Blöschl, MFP Bierkens, A Chambel, C Cudennec, G Destouni, A Fiori, ... Hydrological Sciences Journal 64 (10), 1141-1158, 2019	693	2019
A brief review of random forests for water scientists and practitioners and their recent history in water resources H Tyralis, G Papacharalampous, A Langousis Water 11 (5), 910, 2019	479*	2019
Variable selection in time series forecasting using random forests H Tyralis, G Papacharalampous Algorithms 10 (4), 114, 2017	193	2017
Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes G Papacharalampous, H Tyralis, D Koutsoyiannis Stochastic Environmental Research and Risk Assessment 33 (2), 481-514, 2019	150	2019
Predictability of monthly temperature and precipitation using automatic time series forecasting methods G Papacharalampous, H Tyralis, D Koutsoyiannis Acta Geophysica 66 (4), 807-831, 2018	136	2018
Super ensemble learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms H Tyralis, G Papacharalampous, A Langousis Neural Computing and Applications 33 (8), 3053-3068, 2021	129	2021
Simultaneous estimation of the parameters of the Hurst–Kolmogorov stochastic process H Tyralis, D Koutsoyiannis Stochastic Environmental Research and Risk Assessment 25 (1), 21-33, 2011	100	2011
Evaluation of random forests and Prophet for daily streamflow forecasting G Papacharalampous, H Tyralis Advances in Geosciences 45, 201-208, 2018	90*	2018
Hydrological post-processing using stacked generalization of quantile regression algorithms: Large-scale application over CONUS H Tyralis, G Papacharalampous, A Burnetas, A Langousis Journal of Hydrology 577, 123957, 2019	83	2019
Univariate time series forecasting of temperature and precipitation with a focus on machine learning algorithms: A multiple-case study from Greece G Papacharalampous, H Tyralis, D Koutsoyiannis Water Resources Management 32 (15), 5207-5239, 2018	75	2018
Probabilistic hydrological post-processing at scale: Why and how to apply machine-learning quantile regression algorithms G Papacharalampous, H Tyralis, A Langousis, AW Jayawardena, ... Water 11 (10), 2126, 2019	59	2019
Accuracy measurement of random forests and linear regression for mass appraisal models that estimate the prices of residential apartments in Nicosia, Cyprus T Dimopoulos, H Tyralis, NP Bakas, D Hadjimitsis Advances in Geosciences 45, 377-382, 2018	53	2018
How to explain and predict the shape parameter of the generalized extreme value distribution of streamflow extremes using a big dataset H Tyralis, G Papacharalampous, S Tantanee Journal of Hydrology 574, 628-645, 2019	51	2019
A Bayesian statistical model for deriving the predictive distribution of hydroclimatic variables H Tyralis, D Koutsoyiannis Climate Dynamics 42 (11-12), 2867-2883, 2014	48	2014
Boosting algorithms in energy research: A systematic review H Tyralis, G Papacharalampous Neural Computing and Applications 33 (21), 14101-14117, 2021	46	2021
On the long-range dependence properties of annual precipitation using a global network of instrumental measurements H Tyralis, P Dimitriadis, D Koutsoyiannis, PE O'Connell, K Tzouka, ... Advances in Water Resources 111, 301-318, 2018	45	2018
One-step ahead forecasting of geophysical processes within a purely statistical framework G Papacharalampous, H Tyralis, D Koutsoyiannis Geoscience Letters 5 (12), 2018	44*	2018
Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity G Papacharalampous, H Tyralis, SM Papalexiou, A Langousis, S Khatami, ... Science of the Total Environment 767, 144612, 2021	40	2021
HKprocess: Hurst-Kolmogorov process. R package version 0.1-1 H Tyralis https://CRAN.R-project.org/package=HKprocess, 2022	38*	2022
Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale G Papacharalampous, H Tyralis, D Koutsoyiannis, A Montanari Advances in Water Resources 136, 103470, 2020	38	2020

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