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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Da: Books Puddle, New York, NY, U.S.A.
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces the approach of Machine Learning (ML) based predictive models in the design of composite materials to achieve the required properties for certain applications. ML can learn from existing experimental data obtained from very limited number of experiments and subsequently can be trained to find solutions of the complex non-linear, multi-dimensional functional relationships without any prior assumptions about their nature. In this case the ML models can learn from existing experimental data obtained from (1) composite design based on various properties of the matrix material and fillers/reinforcements (2) material processing during fabrication (3) property relationships. Modelling of these relationships using ML methods significantly reduce the experimental work involved in designing new composites, and therefore offer a new avenue for material design and properties. The book caters to students, academics and researchers who are interested in the field of materialcomposite modelling and design.
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Aggiungi al carrelloHardcover. Condizione: Brand New. 204 pages. 9.25x6.10x0.71 inches. In Stock.
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Da: Brook Bookstore On Demand, Napoli, NA, Italia
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Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Singapore|Springer, 2022
ISBN 10: 9811962774 ISBN 13: 9789811962776
Da: moluna, Greven, Germania
EUR 180,07
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book introduces the approach of Machine Learning (ML) based predictive models in the design of composite materials to achieve the required properties for certain applications. ML can learn from existing experimental data obtained from very limited n.
Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore Nov 2022, 2022
ISBN 10: 9811962774 ISBN 13: 9789811962776
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 213,99
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces the approach of Machine Learning (ML) based predictive models in the design of composite materials to achieve the required properties for certain applications. ML can learn from existing experimental data obtained from very limited number of experiments and subsequently can be trained to find solutions of the complex non-linear, multi-dimensional functional relationships without any prior assumptions about their nature. In this case the ML models can learn from existing experimental data obtained from (1) composite design based on various properties of the matrix material and fillers/reinforcements (2) material processing during fabrication (3) property relationships. Modelling of these relationships using ML methods significantly reduce the experimental work involved in designing new composites, and therefore offer a new avenue for material design and properties. The book caters to students, academics and researchers who are interested in the field of materialcomposite modelling and design. 204 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer Nov 2022, 2022
ISBN 10: 9811962774 ISBN 13: 9789811962776
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 213,99
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduces the approach of Machine Learning (ML) based predictive models in the design of composite materials to achieve the required properties for certain applications. ML can learn from existing experimental data obtained from very limited number of experiments and subsequently can be trained to find solutions of the complex non-linear, multi-dimensional functional relationships without any prior assumptions about their nature. In this case the ML models can learn from existing experimental data obtained from (1) composite design based on various properties of the matrix material and fillers/reinforcements (2) material processing during fabrication (3) property relationships. Modelling of these relationships using ML methods significantly reduce the experimental work involved in designing new composites, and therefore offer a new avenue for material design and properties. The book caters to students, academics and researchers who are interested in the field of materialcomposite modelling and design.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 204 pp. Englisch.
Da: Majestic Books, Hounslow, Regno Unito
EUR 301,47
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 300,45
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