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Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 2nd edition. 9.44x6.61 inches. In Stock.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 66,58
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 65,59
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Añadir al carritoCondición: New. 2023rd edition NO-PA16APR2015-KAP.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 55,85
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 70,29
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Añadir al carritoCondición: New. Second Edition 2025 NO-PA16APR2015-KAP.
Publicado por Springer International Publishing Mär 2024, 2024
ISBN 10: 3031222512 ISBN 13: 9783031222511
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 42,79
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book enables readers to understand, model, and predict complex dynamical systems using new methods with stochastic tools. The author presents a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. An emphasis is placed on the balance between computational efficiency and modeling accuracy, providing readers with ideas to build useful models in practice. Successful modeling of complex systems requires a comprehensive use of qualitative and quantitative modeling approaches, novel efficient computational methods, physical intuitions and thinking, as well as rigorous mathematical theories. As such, mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools are presented. Both theoretical and numerical approaches are included, allowing readers to choose suitable methods in different practical situations. The author provides practical examples and motivations when introducing various mathematical and stochastic tools and merges mathematics, statistics, information theory, computational science, and data science. In addition, the author discusses how to choose and apply suitable mathematical tools to several disciplines including pure and applied mathematics, physics, engineering, neural science, material science, climate and atmosphere, ocean science, and many others. Readers will not only learn detailed techniques for stochastic modeling and prediction, but will develop their intuition as well. Important topics in modeling and prediction including extreme events, high-dimensional systems, and multiscale features are discussed.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 56,71
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Publicado por Springer Nature Switzerland, Springer Nature Switzerland Apr 2025, 2025
ISBN 10: 3031819233 ISBN 13: 9783031819230
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 42,79
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This Second Edition is an essential guide to understanding, modeling, and predicting complex dynamical systems using new methods with stochastic tools. Expanding upon the original book, the author covers a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. The author presents mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools. The book provides practical examples and motivations when introducing these tools, merging mathematics, statistics, information theory, computational science, and data science. The author emphasizes the balance between computational efficiency and modeling accuracy while equipping readers with the skills to choose and apply stochastic tools to a wide range of disciplines. This second edition includes updated discussion of combining stochastic models with machine learning and addresses several additional topics, including importance sampling, regression, and maximum likelihood estimate. The author also introduces a new chapter on optimal control.
Publicado por Springer International Publishing, 2023
ISBN 10: 3031222482 ISBN 13: 9783031222481
Idioma: Inglés
Librería: Buchpark, Trebbin, Alemania
EUR 31,23
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Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Seiten: 216 | Sprache: Englisch | Produktart: Bücher.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 60,20
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 56,60
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por Springer, Berlin, Springer International Publishing, Springer, 2024
ISBN 10: 3031222512 ISBN 13: 9783031222511
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 42,79
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book enables readers to understand, model, and predict complex dynamical systems using new methods with stochastic tools. The author presents a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. An emphasis is placed on the balance between computational efficiency and modeling accuracy, providing readers with ideas to build useful models in practice. Successful modeling of complex systems requires a comprehensive use of qualitative and quantitative modeling approaches, novel efficient computational methods, physical intuitions and thinking, as well as rigorous mathematical theories. As such, mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools are presented. Both theoretical and numerical approaches are included, allowing readers to choose suitable methods in different practical situations. The author provides practical examples and motivations when introducing various mathematical and stochastic tools and merges mathematics, statistics, information theory, computational science, and data science. In addition, the author discusses how to choose and apply suitable mathematical tools to several disciplines including pure and applied mathematics, physics, engineering, neural science, material science, climate and atmosphere, ocean science, and many others. Readers will not only learn detailed techniques for stochastic modeling and prediction, but will develop their intuition as well. Important topics in modeling and prediction including extreme events, high-dimensional systems, and multiscale features are discussed. 199 pp. Englisch.
Publicado por Springer Nature Switzerland, Springer Nature Switzerland Apr 2025, 2025
ISBN 10: 3031819233 ISBN 13: 9783031819230
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 42,79
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Second Edition is an essential guide to understanding, modeling, and predicting complex dynamical systems using new methods with stochastic tools. Expanding upon the original book, the author covers a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. The author presents mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools. The book provides practical examples and motivations when introducing these tools, merging mathematics, statistics, information theory, computational science, and data science. The author emphasizes the balance between computational efficiency and modeling accuracy while equipping readers with the skills to choose and apply stochastic tools to a wide range of disciplines. This second edition includes updated discussion of combining stochastic models with machine learning and addresses several additional topics, including importance sampling, regression, and maximum likelihood estimate. The author also introduces a new chapter on optimal control. 244 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 66,44
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Librería: Majestic Books, Hounslow, Reino Unido
EUR 70,20
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 67,83
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 70,68
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Librería: moluna, Greven, Alemania
EUR 38,69
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.