Stochastic Methods for Modeling and Predicting Complex Dynamical Systems

Name: Stochastic Methods for Modeling and Predicting Complex Dynamical Systems
Brand: Springer, Berlin
SKU: 9783031819230
Price: 46.49 EUR
Availability: InStock

Uncertainty Quantification, State Estimation, and Reduced-Order Models

Автор: Nan Chen

Език:

Корици: С твърди корици

Издател: Springer, Berlin

Наличност: Външен склад

Изпращаме след 10-13 дни

46.49 € 90.92 лв

This second edition is an essential guide to understanding, modeling, and predicting complex dynamic...

Информация за книгата

Автор

Nan Chen

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2025

страници

220

EAN

9783031819230

Enbook ID

47021512

Издател

Springer, Berlin

Теглоt

529

Размери

168 x 240

Пълно описание

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.

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