Stochastic methods modeling predicting de chen nan (15 resultados)

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  • Idioma: Inglés

    Editorial: Springer, 2023

    3031222482 / 9783031222481

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    Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International

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    Condición: Nuevo

    EUR 49,24

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    Cantidad disponible: 1 disponibles

    Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

  • Idioma: Inglés

    Editorial: Springer, 2023

    3031222504 / 9783031222504

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    Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections

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    Condición: Nuevo

    EUR 54,87

    Envío por EUR 10,93 
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    Cantidad disponible: Más de 20 disponibles

    Condición: New. In English.

  • Idioma: Inglés

    Editorial: Springer, 2026

    3031819268 / 9783031819261

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 69,83

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    Cantidad disponible: 1 disponibles

    Taschenbuch. 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.

  • Idioma: Inglés

    Editorial: Springer, 2025

    3031819233 / 9783031819230

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 71,46

    Envío por EUR 30,50 
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    Cantidad disponible: 1 disponibles

    Buch. 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.

  • Idioma: Inglés

    Editorial: Springer, 2026

    3031819268 / 9783031819261

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Condición: Nuevo

    EUR 45,95

    Envío por EUR 70,00 
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    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Stochastic Methods for Modeling and Predicting Complex Dynamical Systems | Uncertainty Quantification, State Estimation, and Reduced-Order Models | Nan Chen | Taschenbuch | Synthesis Lectures on Mathematics & Statistics | xvi | Englisch | 2026 | Springer | EAN 9783031819261 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Idioma: Inglés

    Editorial: Springer International Publishing, 2023

    3031222482 / 9783031222481

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    Librería: Buchpark, Trebbin, AlemaniaBuchpark

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    Condición: Usado

    EUR 35,28

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    Cantidad disponible: 3 disponibles

    Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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.

  • Idioma: Inglés

    Editorial: Springer International Publishing, 2023

    3031222482 / 9783031222481

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    Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, AlemaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer

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    Condición: Usado - Bueno

    EUR 189,00

    Envío por EUR 39,95 
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    Cantidad disponible: 1 disponibles

    Hardcover. Condición: gut. 2023. Stochastic Methods for Modeling and Predicting Complex Dynamical Systems In deutscher Sprache. pages.

  • Idioma: Inglés

    Editorial: Springer, 2025

    3031819233 / 9783031819230

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    Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    Condición: Nuevo

    EUR 42,22

    Envío por EUR 6,80 
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    Cantidad disponible: Más de 20 disponibles

    Condición: new. Questo è un articolo print on demand.

  • Idioma: Inglés

    Editorial: Springer Nature B.V., 2023

    3031222504 / 9783031222504

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    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

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    Condición: Nuevo

    EUR 58,43

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    Cantidad disponible: Más de 20 disponibles

    PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Springer Nature B.V., 2023

    3031222504 / 9783031222504

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    Condición: Nuevo

    EUR 55,44

    Envío por EUR 4,85 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    PAP. 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.

  • Idioma: Inglés

    Editorial: Springer, Springer Apr 2025, 2025

    3031819233 / 9783031819230

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Condición: Nuevo

    EUR 48,14

    Envío por EUR 23,00 
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    Cantidad disponible: 2 disponibles

    Buch. 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.

  • Idioma: Inglés

    Editorial: Springer Apr 2026, 2026

    3031819268 / 9783031819261

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Condición: Nuevo

    EUR 48,14

    Envío por EUR 23,00 
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    Cantidad disponible: 2 disponibles

    Taschenbuch. 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.

  • Idioma: Inglés

    Editorial: Springer Verlag GmbH, 2025

    3031819233 / 9783031819230

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: Nuevo

    EUR 42,96

    Envío por EUR 48,99 
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    Cantidad disponible: Más de 20 disponibles

    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

  • Idioma: Inglés

    Editorial: Springer Apr 2026, 2026

    3031819268 / 9783031819261

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Condición: Nuevo

    EUR 48,14

    Envío por EUR 60,00 
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    Cantidad disponible: 1 disponibles

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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.

  • Idioma: Inglés

    Editorial: Springer, Springer Apr 2025, 2025

    3031819233 / 9783031819230

    • Tapa dura
    • Impresión bajo demanda

    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 48,14

    Envío por EUR 60,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 244 pp. Englisch.