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Ergebnis der Suche nach: "Machine Learning"
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27211 - 27220 von 28857
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Artikel 27211 Signalverarbeitung - Big Data und Digitale Zwillinge beschleunigen die Erprobungsphase
Enthalten in ATZ-Elektronik Bd. 14, 7.6.2019, Nr. 6, date:6.2019: 38-43
Online Ressource
Artikel 27212 Signature-based Adaptive Cloud Resource Usage Prediction Using Machine Learning and Anomaly Detection
Enthalten in Journal of grid computing Bd. 22, 23.4.2024, Nr. 2, date:6.2024: 1-15
Online Ressource
Artikel 27213 Signature-based intrusion detection using machine learning and deep learning approaches empowered with fuzzy clustering
Enthalten in Scientific reports Bd. 15, 11.1.2025, Nr. 1, date:12.2025: 1-33
Online Ressource
Artikel 27214 Signatures of paracrystallinity in amorphous silicon from machine-learning-driven molecular dynamics
Enthalten in Nature Communications Bd. 16, 10.3.2025, Nr. 1, date:12.2025: 1-8
Online Ressource
Artikel 27215 Significance of EMHD graphene oxide (GO) water ethylene glycol nanofluid flow in a Darcy–Forchheimer medium by machine learning algorithm
Enthalten in The European physical journal / Plus Bd. 138, 7.3.2023, Nr. 3, date:3.2023: 1-15
Online Ressource
Artikel 27216 Significance of gender, brain region and EEG band complexity analysis for Parkinson’s disease classification using recurrence plots and machine learning algorithms
Enthalten in Physical and engineering sciences in medicine Bd. 48, 27.1.2025, Nr. 1, date:3.2025: 391-407
Online Ressource
Artikel 27217 Significance of Sequence Features in Classification of Protein–Protein Interactions Using Machine Learning
Enthalten in The protein journal Bd. 43, 19.12.2023, Nr. 1, date:2.2024: 72-83
Online Ressource
Artikel 27218 Silent no more: a comprehensive review of artificial intelligence, deep learning, and machine learning in facilitating deaf and mute communication
Enthalten in Artificial intelligence review Bd. 57, 26.6.2024, Nr. 7, date:7.2024: 1-46
Online Ressource
Artikel 27219 Silica fume as a supplementary cementitious material in pervious concrete: prediction of compressive strength through a machine learning approach
Enthalten in Asian journal of civil engineering Bd. 25, 2.1.2024, Nr. 3, date:4.2024: 2963-2977
Online Ressource
Artikel 27220 Silica sources for arsenic mitigation in rice: machine learning-based predictive modeling and risk assessment
Enthalten in Environmental science and pollution research Bd. 30, 18.10.2023, Nr. 53, date:11.2023: 113660-113673
Online Ressource


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