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Ergebnis der Suche nach: "Machine Learning"
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25411 - 25420 von 29129
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Artikel 25411 Polymer design for solvent separations by integrating simulations, experiments and known physics via machine learning
Enthalten in npj computational materials Bd. 11, 19.6.2025, Nr. 1, date:12.2025: 1-12
Online Ressource
Artikel 25412 Polyolefins in the Circular Economy: Advances and Recyclability
Enthalten in Sustainability & circularity now Bd. 02, 2025, Nr. CP
Online Ressource
Artikel 25413 Population Dynamics and Estimation of Damage of the Spittlebug Aeneolamia varia on Sugarcane in Colombia by Using remote Sensing and Machine Learning Tools
Enthalten in Sugar tech Bd. 25, 20.4.2023, Nr. 5, date:10.2023: 1115-1133
Online Ressource
Artikel 25414 Porosity prediction of tight reservoir rock using well logging data and machine learning
Enthalten in Scientific reports Bd. 15, 16.4.2025, Nr. 1, date:12.2025: 1-17
Online Ressource
Artikel 25415 Porosity prediction using bagging ensemble machine learning in CCUS reservoirs. A case study: Darling Basin, Australia
Enthalten in Earth science informatics Bd. 18, 14.12.2024, Nr. 1, date:1.2025: 1-18
Online Ressource
Artikel 25416 Porosity prediction using ensemble machine learning approaches: A case study from Upper Assam basin
Enthalten in Journal of earth system science Bd. 133, 21.5.2024, Nr. 2, date:6.2024: 1-13
Online Ressource
Artikel 25417 Porous Metal Properties Analysis: A Machine Learning Approach
Enthalten in JOM Bd. 73, 10.6.2021, Nr. 7, date:7.2021: 2039-2049
Online Ressource
Artikel 25418 Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems
Enthalten in Computational mechanics Bd. 72, 21.3.2023, Nr. 3, date:9.2023: 553-561
Online Ressource
Artikel 25419 Portability of semantic and spatial–temporal machine learning methods to analyse social media for near-real-time disaster monitoring
Enthalten in Natural hazards Bd. 108, 10.7.2021, Nr. 3, date:9.2021: 2939-2969
Online Ressource
Artikel 25420 Portable optical spectroscopy and machine learning techniques for quantification of the biochemical content of raw food materials
Enthalten in CABI agriculture and bioscience Bd. 5, 14.4.2024, Nr. 1, date:12.2024: 1-12
Online Ressource


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