Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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881 - 890 von 28260

	881	Hybrid model of 1D-CNN and LSTM for forecasting Ethereum closing prices: a case study of temporal analysis Enthalten in International journal of information technology 26.2.2025: 1-13
	882	Performance evaluation of various electric vehicle drive systems in energy efficient grid integrated renewable systems Enthalten in International journal of information technology 26.2.2025: 1-18
	883	Machine Learning‐Based High‐Throughput Screening, Molecular Modeling and Quantum Chemical Analysis to Investigate Mycobacterium tuberculosis MetRS Inhibitors Enthalten in ChemistryOpen 25.02.2025. 15 S.
	884	Machine Learning‐Driven Mass Discovery and High‐Throughput Screening of Fluoroether‐Based Electrolytes for High‐Stability Lithium Metal Batteries Enthalten in Angewandte Chemie 25.02.2025. 13 S.
	885	Machine Learning‐Driven Mass Discovery and High‐Throughput Screening of Fluoroether‐Based Electrolytes for High‐Stability Lithium Metal Batteries Enthalten in Angewandte Chemie / International edition 25.02.2025. 13 S.
	886	Revolutionizing the Future of Smart Materials: A Review of 4D Printing, Design, Optimization, and Machine Learning Integration Enthalten in Advanced Materials Technologies 25.02.2025. 39 S.
	887	Machine learning-based analysis of workers' exposure and detection to volatile organic compounds (VOC) Enthalten in International journal of environmental science and technology 25.2.2025: 1-17
	888	A Novel Prediction Model for Airfoil Aerodynamic Characteristics Based on Machine Learning Enthalten in Iranian journal of science and technology / Transactions of mechanical engineering 24.2.2025: 1-19
	889	Correction: Semantic Enrichment of a BIM Model Using Revit: Automatic Annotation of Doors in High-Rise Residential Building Models Using Machine Learning Enthalten in Fire technology 24.2.2025: 1
	890	Determining the risk factors for postoperative mechanical complication in degenerative scoliosis: a machine learning approach based on musculoskeletal metrics Enthalten in European spine journal 24.2.2025: 1-11

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