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Ergebnis der Suche nach: "Machine Learning"
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35301 - 35310 von 35943
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Artikel 35301 Triboinformatic Machine Learning Model for Frictional Behavior and Wear Volume Loss Prediction of SS316L Alloy Clad with WC/NiCrBSi
Enthalten in Journal of bio- and tribo-corrosion Bd. 10, 2.7.2024, Nr. 3, date:9.2024: 1-16
Online Ressource
Artikel 35302 Trihalomethane prediction model for water supply system based on machine learning and Log-linear regression
Enthalten in Environmental geochemistry and health Bd. 46, 16.1.2024, Nr. 2, date:2.2024: 1-17
Online Ressource
Artikel 35303 Trimming stability selection increases variable selection robustness
Enthalten in Machine learning Bd. 112, 4.10.2023, Nr. 12, date:12.2023: 4995-5055
Online Ressource
Artikel 35304 Triple A — Wie AI, Automation und Algorithmen die Musikbranche umkrempeln
Enthalten in Digitale Welt Bd. 6, 15.9.2022, Nr. 4, date:10.2022: 91-92
Online Ressource
Artikel 35305 Tropical cyclone intensity classification from infrared images of clouds over Bay of Bengal and Arabian Sea using machine learning classifiers
Enthalten in Arabian journal of geosciences Bd. 14, 8.4.2021, Nr. 8, date:4.2021: 1-17
Online Ressource
Artikel 35306 Trust-driven approach to enhance early forest fire detection using machine learning
Enthalten in Scientific reports Bd. 15, 25.4.2025, Nr. 1, date:12.2025: 1-22
Online Ressource
Artikel 35307 Trusted explainable AI based implementation for detection of neurodegenerative disorders (ND)
Enthalten in International journal of information technology Bd. 17, 9.12.2024, Nr. 2, date:3.2025: 1275-1282
Online Ressource
Artikel 35308 Trustworthy machine learning in the context of security and privacy
Enthalten in International journal of information security Bd. 23, 3.4.2024, Nr. 3, date:6.2024: 2287-2314
Online Ressource
Artikel 35309 Truthful meta-explanations for local interpretability of machine learning models
Enthalten in Applied intelligence Bd. 53, 30.8.2023, Nr. 22, date:11.2023: 26927-26948
Online Ressource
Artikel 35310 TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods
Enthalten in Journal of iron and steel research, international Bd. 31, 4.1.2024, Nr. 1, date:1.2024: 174-194
Online Ressource


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