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Big data approaches and artificial intelligence are rapidly reshaping the way geoscientists analyze, model, and interpret the Earth. This Special Issue focuses on the practical application of big data mining, machine learning, and artificial intelligence in Earth science. It aims to explore the role of big data paradigms in guiding model development, the integration of domain knowledge into AI systems, and the validation of AI methodologies within geoscientific contexts. Comprising 17 papers, the Reprint highlights transformative advances in areas such as mineral prospectivity prediction with metallogenic belt identification, geological data inversion, modeling and deep learning architectures, and combining geological databases with big data mining. It further introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and knowledge discovery. By presenting AI-driven geology as a forward-looking paradigm, the collection demonstrates how artificial intelligence can revolutionize traditional geoscience practices by providing improved accuracy and deeper insight. Through practical examples and case studies, the Reprint illustrates the application of these technologies to complex geoscientific problems. It equips researchers, practitioners, and students with cutting-edge knowledge and tools to harness big data and machine learning, fostering innovation and advancing understanding across the geoscience disciplines.
Titre : Application of Big Data Mining, Machine ...
Éditeur : Mdpi AG
Date d'édition : 2026
Reliure : Couverture rigide
Etat : As New
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
HRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L1-9783725871407
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Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. Big data approaches and artificial intelligence are rapidly reshaping the way geoscientists analyze, model, and interpret the Earth. This Special Issue focuses on the practical application of big data mining, machine learning, and artificial intelligence in Earth science. It aims to explore the role of big data paradigms in guiding model development, the integration of domain knowledge into AI systems, and the validation of AI methodologies within geoscientific contexts. Comprising 17 papers, the Reprint highlights transformative advances in areas such as mineral prospectivity prediction with metallogenic belt identification, geological data inversion, modeling and deep learning architectures, and combining geological databases with big data mining. It further introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and knowledge discovery. By presenting AI-driven geology as a forward-looking paradigm, the collection demonstrates how artificial intelligence can revolutionize traditional geoscience practices by providing improved accuracy and deeper insight. Through practical examples and case studies, the Reprint illustrates the application of these technologies to complex geoscientific problems. It equips researchers, practitioners, and students with cutting-edge knowledge and tools to harness big data and machine learning, fostering innovation and advancing understanding across the geoscience disciplines. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783725871407
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Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
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Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9783725871407
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Vendeur : CitiRetail, Stevenage, Royaume-Uni
Hardcover. Etat : new. Hardcover. Big data approaches and artificial intelligence are rapidly reshaping the way geoscientists analyze, model, and interpret the Earth. This Special Issue focuses on the practical application of big data mining, machine learning, and artificial intelligence in Earth science. It aims to explore the role of big data paradigms in guiding model development, the integration of domain knowledge into AI systems, and the validation of AI methodologies within geoscientific contexts. Comprising 17 papers, the Reprint highlights transformative advances in areas such as mineral prospectivity prediction with metallogenic belt identification, geological data inversion, modeling and deep learning architectures, and combining geological databases with big data mining. It further introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and knowledge discovery. By presenting AI-driven geology as a forward-looking paradigm, the collection demonstrates how artificial intelligence can revolutionize traditional geoscience practices by providing improved accuracy and deeper insight. Through practical examples and case studies, the Reprint illustrates the application of these technologies to complex geoscientific problems. It equips researchers, practitioners, and students with cutting-edge knowledge and tools to harness big data and machine learning, fostering innovation and advancing understanding across the geoscience disciplines. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9783725871407
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Big data approaches and artificial intelligence are rapidly reshaping the way geoscientists analyze, model, and interpret the Earth. This Special Issue focuses on the practical application of big data mining, machine learning, and artificial intelligence in Earth science. It aims to explore the role of big data paradigms in guiding model development, the integration of domain knowledge into AI systems, and the validation of AI methodologies within geoscientific contexts. Comprising 17 papers, the Reprint highlights transformative advances in areas such as mineral prospectivity prediction with metallogenic belt identification, geological data inversion, modeling and deep learning architectures, and combining geological databases with big data mining. It further introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and knowledge discovery. By presenting AI-driven geology as a forward-looking paradigm, the collection demonstrates how artificial intelligence can revolutionize traditional geoscience practices by providing improved accuracy and deeper insight. Through practical examples and case studies, the Reprint illustrates the application of these technologies to complex geoscientific problems. It equips researchers, practitioners, and students with cutting-edge knowledge and tools to harness big data and machine learning, fostering innovation and advancing understanding across the geoscience disciplines. N° de réf. du vendeur 9783725871407
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Vendeur : AussieBookSeller, Truganina, VIC, Australie
Hardcover. Etat : new. Hardcover. Big data approaches and artificial intelligence are rapidly reshaping the way geoscientists analyze, model, and interpret the Earth. This Special Issue focuses on the practical application of big data mining, machine learning, and artificial intelligence in Earth science. It aims to explore the role of big data paradigms in guiding model development, the integration of domain knowledge into AI systems, and the validation of AI methodologies within geoscientific contexts. Comprising 17 papers, the Reprint highlights transformative advances in areas such as mineral prospectivity prediction with metallogenic belt identification, geological data inversion, modeling and deep learning architectures, and combining geological databases with big data mining. It further introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and knowledge discovery. By presenting AI-driven geology as a forward-looking paradigm, the collection demonstrates how artificial intelligence can revolutionize traditional geoscience practices by providing improved accuracy and deeper insight. Through practical examples and case studies, the Reprint illustrates the application of these technologies to complex geoscientific problems. It equips researchers, practitioners, and students with cutting-edge knowledge and tools to harness big data and machine learning, fostering innovation and advancing understanding across the geoscience disciplines. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9783725871407
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Vendeur : preigu, Osnabrück, Allemagne
Buch. Etat : Neu. Application of Big Data Mining, Machine Learning and Artificial Intelligence in Geoscience, 2nd Edition | Buch | Englisch | 2026 | MDPI AG | EAN 9783725871407 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 135166498
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Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. N° de réf. du vendeur 26406562935
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand. N° de réf. du vendeur 407639976
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