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Neuigkeiten Vom 10. September 2025, 13 Uhr, bis 11. September 2025, 22 Uhr, kann es zu Einschränkungen bei der Bereitstellung von Medienwerken kommen. Wir informieren Sie per E-Mail über den aktuellen Stand Ihrer Bestellungen. // From 13:00 on 10 September 2025 until 22:00 on 11 September 2025, there may be restrictions on the provision of media works. We will inform you by email about the current status of your orders.
 
 
 


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Artikel 121 Smart adaptive run parameterization (SArP): enhancement of user manual selection of running parameters in fluid dynamic simulations using bio-inspired and machine-learning techniques
Enthalten in Soft computing 19.1.2019: 1-17
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Artikel 122 Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques
Enthalten in Geoscientific model development discussions 2019: 1-48
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Artikel 123 Predicting wildfire burned area in South Central US using integrated machine learning techniques
Enthalten in Atmospheric chemistry and physics / Discussions 2019: 1-25
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Artikel 124 InDel marker detection by integration of multiple softwares using machine learning techniques
Enthalten in BMC bioinformatics 2.11.2016: 1-11
Online Ressource
Artikel 125 Phase segmentation of X-ray computer tomography rock images using machine learning techniques: an accuracy and performance study
Enthalten in Solid earth Bd. 7, 2016, Nr. 4: 1125-1139
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Artikel 126 Predicting firefighters' exertion based on machine learning techniques
Enthalten in Baua: Fokus 2016: 1-13
Online Ressource
Online Ressourcen 127 Mining Scientific Articles Powered by Machine Learning Techniques
Gulo, Carlos A. S. J.. - Wadern : Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2015
Online Ressource
Artikel 128 Assessment of machine-learning techniques on large pathology data sets to address assay redundancy in routine liver function test profiles
Enthalten in Diagnosis Bd. 2, 2015, Nr. 1: 41-51. 11 S.
Online Ressource
Online Ressourcen 129 Applying Machine Learning Techniques to ASP Solving
Maratea, Marco. - Wadern : Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2012
Online Ressource
Artikel 130 Machine learning techniques applied to prediction of residual strength of clay
Enthalten in Open Geosciences Bd. 3, 2011, Nr. 4: 449-461. 13 S.
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