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Advances Subsurface Data Analytics (14 results)
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paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Condition: New. pp. 376.
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Condition: New. pp. 376.
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Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches
Published by Elsevier Science Publishing Co Inc, 2022
ISBN 10: 0128222956 ISBN 13: 9780128222959
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 222.
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Condition: New. pp. 376.
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Advances in Subsurface Data Analytics: Traditional and Physics-Based Machine Learning
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Advances in Subsurface Data Analytics : Traditional and Physics-based Machine Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: As New. Unread book in perfect condition.
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Advances in Subsurface Data Analytics : Traditional and Physics-based Machine Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Condition: New. Covers fundamentals of simple machine learning and deep learning algorithms, and physics-based approaches written by practitioners in academia and industry Presents detailed case studies of individual machine learning algorithms and optima.
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Advances in Subsurface Data Analytics
Published by Elsevier Science Publishing Co Inc Mai 2022, 2022
ISBN 10: 0128222956 ISBN 13: 9780128222959
Language: English
Taschenbuch. Condition: Neu. Neuware - Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume.
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Condition: new. Questo è un articolo print on demand.
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Paperback. Condition: Brand New. 400 pages. 9.25x7.50x0.85 inches. In Stock. This item is printed on demand.
