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Bestimmung von Soiling aus Betriebs- und Meteodaten

Brenner, Alex (2021) Bestimmung von Soiling aus Betriebs- und Meteodaten. AG3-Workshop: Maschinelles Lernen & KI für CSP, online.

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Item URL in elib:https://elib.dlr.de/146987/
Document Type:Conference or Workshop Item (Speech)
Title:Bestimmung von Soiling aus Betriebs- und Meteodaten
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Brenner, AlexUNSPECIFIEDhttps://orcid.org/0000-0003-0754-0272
Date:8 December 2021
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Parabolrinnne, Spiegelverschmutzung, Soiling, Künstliche Intelligenz, Machine learning, Neuronales Netz
Event Title:AG3-Workshop: Maschinelles Lernen & KI für CSP
Event Location:online
Event Type:Workshop
HGF - Research field:Energy
HGF - Program:Materials and Technologies for the Energy Transition
HGF - Program Themes:High-Temperature Thermal Technologies
DLR - Research area:Energy
DLR - Program:E SW - Solar and Wind Energy
DLR - Research theme (Project):E - Advanced Heat Transfer Media
Location: Stuttgart
Institutes and Institutions:Institute of Solar Research > Solar High Temperature Technologies
Deposited By: Brenner, Alex
Deposited On:13 Dec 2021 14:40
Last Modified:13 Dec 2021 14:40

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