| 000 | 04859nam a22006135i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-22249-8 | ||
| 003 | DE-He213 | ||
| 005 | 20240730164445.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 230313s2023 sz | s |||| 0|eng d | ||
| 020 |
_a9783031222498 _9978-3-031-22249-8 |
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| 024 | 7 |
_a10.1007/978-3-031-22249-8 _2doi |
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| 050 | 4 | _aQA274-274.9 | |
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_aPBT _2bicssc |
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_a003.76 _223 |
| 100 | 1 |
_aChen, Nan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _984592 |
|
| 245 | 1 | 0 |
_aStochastic Methods for Modeling and Predicting Complex Dynamical Systems _h[electronic resource] : _bUncertainty Quantification, State Estimation, and Reduced-Order Models / _cby Nan Chen. |
| 250 | _a1st ed. 2023. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2023. |
|
| 300 |
_aXVI, 199 p. 37 illus., 36 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aSynthesis Lectures on Mathematics & Statistics, _x1938-1751 |
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| 505 | 0 | _aIntroduction to Complex Systems, Stochastic Methods, and Model Error -- Basic Stochastic Toolkits -- Introduction to Information Theory -- Numerical Schemes for Solving Stochastic Differential Equations -- Gaussian and Non-Gaussian Processes -- Data Assimilation -- Simple Data-driven Stochastic Models -- Conditional Gaussian Nonlinear Systems -- Parameter Estimation with Uncertainty Quantification -- Ensemble Forecast -- Combining Stochastic Models with Machine Learning. . | |
| 520 | _aThis 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. In addition, this book: Combines qualitative and quantitative modeling and efficient computational methods; Presents topics from nonlinear dynamics, stochastic modeling, numerical algorithms, and real applications; Includes MATLAB® codes for the provided examples to help readers better understand and apply the concepts. | ||
| 650 | 0 |
_aStochastic processes. _93246 |
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| 650 | 0 |
_aStochastic models. _913059 |
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| 650 | 0 |
_aSystem theory. _93409 |
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| 650 | 0 |
_aMathematics. _911584 |
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| 650 | 0 |
_aArtificial intelligence _xData processing. _921787 |
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| 650 | 0 |
_aComputer science. _99832 |
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| 650 | 1 | 4 |
_aStochastic Systems and Control. _984595 |
| 650 | 2 | 4 |
_aStochastic Modelling. _984596 |
| 650 | 2 | 4 |
_aComplex Systems. _918136 |
| 650 | 2 | 4 |
_aApplications of Mathematics. _931558 |
| 650 | 2 | 4 |
_aData Science. _934092 |
| 650 | 2 | 4 |
_aModels of Computation. _931806 |
| 710 | 2 |
_aSpringerLink (Online service) _984597 |
|
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031222481 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031222504 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031222511 |
| 830 | 0 |
_aSynthesis Lectures on Mathematics & Statistics, _x1938-1751 _984599 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-22249-8 |
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| 942 | _cEBK | ||
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