dc.contributor.advisor	Sándor, Baran
dc.contributor.author	Mehrez, El Ayari
dc.contributor.department	Informatikai tudományok doktori iskola	hu
dc.contributor.submitterdep	DE--Informatikai Kar -- Az információ technológia és a sztochasztikus rendszerek elméleti alapjai és alkalmazásai
dc.date.accessioned	2022-04-24T22:04:39Z
dc.date.available	2022-04-24T22:04:39Z
dc.date.defended	2022-06-10T11:00:00Z
dc.date.issued	2022
dc.description.abstract	The goal of this thesis is to present a newly developed probabilistic post-processing models for ensemble weather forecasts , specifically for water level, solar irradiance and total cloud cover.	hu_HU
dc.format.extent	123	hu_HU
dc.identifier.uri	http://hdl.handle.net/2437/331395
dc.language.iso	en	hu_HU
dc.subject	Ensemble post-processing	hu_HU
dc.subject	Probabilistic forecasting
dc.subject	Machine Learning
dc.subject.discipline	Informatikai tudományok	hu
dc.subject.sciencefield	Műszaki tudományok	hu
dc.title	Post-processing of Ensemble Forecasts of Various Weather and Hydrological Quantities Using Statistical and Machine Learning Methods	hu_HU
dc.title.translated	Post-processing of Ensemble Forecasts of Various Weather and Hydrological Quantities Using Statistical and Machine Learning Methods	hu_HU
dc.type	PhD, doktori értekezés	hu

Post-processing of Ensemble Forecasts of Various Weather and Hydrological Quantities Using Statistical and Machine Learning Methods