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Añadir al carritoHardback. Condición: New. New copy - Usually dispatched within 4 working days.
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Añadir al carritoCondición: New. Prof. Mohamed Fathy El-Amin Mousa is a distinguished full professor of applied mathematics and computational sciences at Effat University, Saudi Arabia, and Aswan University, Egypt. With a career spanning more than 25 years, Dr. El-Amin has establ.
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Añadir al carritoHardcover. Condición: Brand New. 272 pages. 9.19x6.13x9.21 inches. In Stock.
Idioma: Inglés
Publicado por Taylor & Francis Ltd Mär 2026, 2026
ISBN 10: 1032747390 ISBN 13: 9781032747392
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Añadir al carritoBuch. Condición: Neu. Neuware - The rapid growth of machine learning in recent years has made it a popular tool for data analysis, modeling, and predictions. As more data is generated from fluid flow simulations and experiments, the use of machine learning algorithms has become essential in making sense of it all. Advances and Applications of Machine Learning in Fluid Flow Problems provides insight into the effective use of machine learning in fluid flow and its potential impact on the field. It examines the application of machine learning techniques in various fluid flow problems, including but not limited to turbulent flow, multiphase flow, complex geometries, flow control, turbulence modeling, particle-fluid interactions, numerical simulations, data-driven modeling, flow in porous media, oil/gas reservoir simulation, permeability prediction, and more. It serves as a useful tool for a wide range of readers in the professional, industrial, and academic sectors.
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Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032747390 ISBN 13: 9781032747392
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Añadir al carritoHardcover. Condición: new. Hardcover. The rapid growth of machine learning in recent years has made it a popular tool for data analysis, modeling, and predictions. As more data is generated from fluid flow simulations and experiments, the use of machine learning algorithms has become essential in making sense of it all. Advances and Applications of Machine Learning in Fluid Flow Problems provides insight into the effective use of machine learning in fluid flow and its potential impact on the field. It examines the application of machine learning techniques in various fluid flow problems, including but not limited to turbulent flow, multiphase flow, complex geometries, flow control, turbulence modeling, particle-fluid interactions, numerical simulations, data-driven modeling, flow in porous media, oil/gas reservoir simulation, permeability prediction, and more. It serves as a useful tool for a wide range of readers in the professional, industrial, and academic sectors.Covers both the theories and practical applications of machine learning in fluid flow problems, making the book a unique and valuable resource for professionals and researchers in the field.Provides a comprehensive examination of the application of machine learning for all aspects of fluid flow problems. The rapid growth of machine learning in recent years has made it a popular tool for data analysis, modeling, and prediction. As more data is generated from fluid flow simulations and experiments, the use of machine learning algorithms has become essential in making sense of it all. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032747390 ISBN 13: 9781032747392
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Añadir al carritoHardcover. Condición: new. Hardcover. The rapid growth of machine learning in recent years has made it a popular tool for data analysis, modeling, and predictions. As more data is generated from fluid flow simulations and experiments, the use of machine learning algorithms has become essential in making sense of it all. Advances and Applications of Machine Learning in Fluid Flow Problems provides insight into the effective use of machine learning in fluid flow and its potential impact on the field. It examines the application of machine learning techniques in various fluid flow problems, including but not limited to turbulent flow, multiphase flow, complex geometries, flow control, turbulence modeling, particle-fluid interactions, numerical simulations, data-driven modeling, flow in porous media, oil/gas reservoir simulation, permeability prediction, and more. It serves as a useful tool for a wide range of readers in the professional, industrial, and academic sectors.Covers both the theories and practical applications of machine learning in fluid flow problems, making the book a unique and valuable resource for professionals and researchers in the field.Provides a comprehensive examination of the application of machine learning for all aspects of fluid flow problems. The rapid growth of machine learning in recent years has made it a popular tool for data analysis, modeling, and prediction. As more data is generated from fluid flow simulations and experiments, the use of machine learning algorithms has become essential in making sense of it all. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032747390 ISBN 13: 9781032747392
Librería: AussieBookSeller, Truganina, VIC, Australia
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Añadir al carritoHardcover. Condición: new. Hardcover. The rapid growth of machine learning in recent years has made it a popular tool for data analysis, modeling, and predictions. As more data is generated from fluid flow simulations and experiments, the use of machine learning algorithms has become essential in making sense of it all. Advances and Applications of Machine Learning in Fluid Flow Problems provides insight into the effective use of machine learning in fluid flow and its potential impact on the field. It examines the application of machine learning techniques in various fluid flow problems, including but not limited to turbulent flow, multiphase flow, complex geometries, flow control, turbulence modeling, particle-fluid interactions, numerical simulations, data-driven modeling, flow in porous media, oil/gas reservoir simulation, permeability prediction, and more. It serves as a useful tool for a wide range of readers in the professional, industrial, and academic sectors.Covers both the theories and practical applications of machine learning in fluid flow problems, making the book a unique and valuable resource for professionals and researchers in the field.Provides a comprehensive examination of the application of machine learning for all aspects of fluid flow problems. The rapid growth of machine learning in recent years has made it a popular tool for data analysis, modeling, and prediction. As more data is generated from fluid flow simulations and experiments, the use of machine learning algorithms has become essential in making sense of it all. 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.