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Stochastic Methods for Modeling and Predicting Complex Dynamical Systems - Uncertainty Quantification, State Estimation, and Reduced-Order Models (Hardcover, 1st ed. 2023)
Loot Price: R989
Discovery Miles 9 890
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Stochastic Methods for Modeling and Predicting Complex Dynamical Systems - Uncertainty Quantification, State Estimation, and Reduced-Order Models (Hardcover, 1st ed. 2023)
Series: Synthesis Lectures on Mathematics & Statistics
Expected to ship within 9 - 15 working days
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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.
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