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Complex dynamical systems are explored through a blend of qualitative and quantitative modeling techniques, emphasizing computational efficiency and accuracy. The author introduces innovative stochastic tools and rigorous mathematical theories, providing both theoretical and numerical approaches for practical applications. Readers gain insights into modeling extreme events, high-dimensional systems, and multiscale features, while learning to apply these methods across various fields such as physics, engineering, and climate science. Practical examples enhance understanding and intuition in stochastic modeling and prediction.
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Stochastic Methods for Modeling and Predicting Complex Dynamical Systems, Nan Chen
- Taal
- Jaar van publicatie
- 2024
- product-detail.submit-box.info.binding
- (Paperback)
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- Ondertitel
- Uncertainty Quantification, State Estimation, and Reduced-Order Models
- Taal
- Engels
- Auteurs
- Nan Chen
- Jaar van publicatie
- 2024
- Formaat
- Paperback
- Aantal pagina's
- 216
- ISBN13
- 9783031222511
- Reeks
- Aantekening
- Complex dynamical systems are explored through a blend of qualitative and quantitative modeling techniques, emphasizing computational efficiency and accuracy. The author introduces innovative stochastic tools and rigorous mathematical theories, providing both theoretical and numerical approaches for practical applications. Readers gain insights into modeling extreme events, high-dimensional systems, and multiscale features, while learning to apply these methods across various fields such as physics, engineering, and climate science. Practical examples enhance understanding and intuition in stochastic modeling and prediction.