Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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531 - 540 von 28321

	531	FFS-IML: fusion-based statistical feature selection for machine learning-driven interpretability of chronic kidney disease Enthalten in International journal of machine learning and cybernetics 21.4.2025: 1-34
	532	From microbial data to forensic insights: systematic review of machine learning models for PMI estimation Enthalten in Forensic science, medicine, and pathology 21.4.2025: 1-30
	533	Innovative Machine Learning, Isotopic, and Hydrogeochemical Techniques for Groundwater Analysis in Arid Landscapes in Egypt’s Eastern Desert Enthalten in Earth systems and environment 21.4.2025: 1-25
	534	Repeated game theory kernel for support vector machine Enthalten in International journal of information technology 21.4.2025: 1-16
	535	Estimation of Bridge Pier Scour Depth Under Clear Water and Live Bed Scouring Conditions Using MARS and ETR Machine Learning Technique Enthalten in Iranian journal of science and technology / Transactions of civil engineering 20.4.2025: 1-27
	536	Microstructural Analysis of Ceramic Materials Through Machine Learning Techniques: A Benchmarking Interdisciplinary Review for Ceramic Material Characterization Enthalten in Institution of Engineers, India. Karnataka State Centre: Journal of the Institution of Engineers (India) / Series D 20.4.2025: 1-19
	537	Hybrid Machine Learning Based Strength and Durability Predictions of Polypropylene Fiber-Reinforced Graphene Oxide Based High-Performance Concrete Enthalten in Iranian journal of science and technology / Transactions of civil engineering 19.4.2025: 1-21
	538	Optimizing multi-physics variables in wire arc additive manufacturing for weld bead aspect ratio: a machine learning approach Enthalten in Progress in additive manufacturing 19.4.2025: 1-15
	539	Predicting antibacterial effects of ozone treatment on green leafy vegetables using machine learning models Enthalten in European food research and technology 19.4.2025: 1-11
	540	QMGBP-DL: a deep learning and machine learning approach for quantum molecular graph band-gap prediction Enthalten in Molecular diversity 19.4.2025: 1-15

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