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Stochastic Methods for Modeling and Predicting Complex Dynamical Systems, Chen


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Автор: Chen
Название:  Stochastic Methods for Modeling and Predicting Complex Dynamical Systems
ISBN: 9783031222481
Издательство: Springer
Классификация:




ISBN-10: 3031222482
Обложка/Формат: Hardback
Страницы: 199
Вес: 0.82 кг.
Дата издания: 09.02.2023
Серия: Synthesis Lectures on Mathematics & Statistics
Язык: English
Издание: 1st ed. 2023
Иллюстрации: 35 tables, color; 36 illustrations, color; 1 illustrations, black and white; xvi, 199 p. 37 illus., 36 illus. in color.
Размер: 245 x 173 x 19
Читательская аудитория: Professional & vocational
Основная тема: Mathematics
Подзаголовок: Uncertainty quantification, state estimation, and reduced-order models
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.
Дополнительное описание: Introduction 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 Assimilati



Social Media Analytics in Predicting Consumer Behavior

Автор: Sumer, Selay Ilgaz
Название: Social Media Analytics in Predicting Consumer Behavior
ISBN: 1032059907 ISBN-13(EAN): 9781032059907
Издательство: Taylor&Francis
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Цена: 22202.00 р.
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Описание: Understanding the importance of social media analytics. Comprehending the role of social media analytics in predicting consumer behavior. Understanding the importance of using social media in strategic marketing plans.

Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems

Автор: M. Reza Rahimi Tabar
Название: Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems
ISBN: 3030184714 ISBN-13(EAN): 9783030184711
Издательство: Springer
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Цена: 16070.00 р.
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Описание: This book focuses on a central question in the field of complex systems: Given a fluctuating (in time or space), uni- or multi-variant sequentially measured set of experimental data (even noisy data), how should one analyse non-parametrically the data, assess underlying trends, uncover characteristics of the fluctuations (including diffusion and jump contributions), and construct a stochastic evolution equation?Here, the term 'non-parametrically' exemplifies that all the functions and parameters of the constructed stochastic evolution equation can be determined directly from the measured data.The book provides an overview of methods that have been developed for the analysis of fluctuating time series and of spatially disordered structures. Thanks to its feasibility and simplicity, it has been successfully applied to fluctuating time series and spatially disordered structures of complex systems studied in scientific fields such as physics, astrophysics, meteorology, earth science, engineering, finance, medicine and the neurosciences, and has led to a number of important results.The book also includes the numerical and analytical approaches to the analyses of complex time series that are most common in the physical and natural sciences. Further, it is self-contained and readily accessible to students, scientists, and researchers who are familiar with traditional methods of mathematics, such as ordinary, and partial differential equations.The codes for analysing continuous time series are available in an R package developed by the research group Turbulence, Wind energy and Stochastic (TWiSt) at the Carl von Ossietzky University of Oldenburg under the supervision of Prof. Dr. Joachim Peinke. This package makes it possible to extract the (stochastic) evolution equation underlying a set of data or measurements.

Generalized Statistical Thermodynamics

Автор: Themis Matsoukas
Название: Generalized Statistical Thermodynamics
ISBN: 3030041484 ISBN-13(EAN): 9783030041489
Издательство: Springer
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Цена: 25155.00 р.
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Описание: This book gives the definitive mathematical answer to what thermodynamics really is: a variational calculus applied to probability distributions. Extending Gibbs's notion of ensemble, the Author imagines the ensemble of all possible probability distributions and assigns probabilities to them by selection rules that are fairly general. The calculus of the most probable distribution in the ensemble produces the entire network of mathematical relationships we recognize as thermodynamics. The first part of the book develops the theory for discrete and continuous distributions while the second part applies this thermodynamic calculus to problems in population balance theory and shows how the emergence of a giant component in aggregation, and the shattering transition in fragmentation may be treated as formal phase transitions.While the book is intended as a research monograph, the material is self-contained and the style sufficiently tutorial to be accessible for self-paced study by an advanced graduate student in such fields as physics, chemistry, and engineering.

Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology

Автор: David Holcman
Название: Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology
ISBN: 3319626264 ISBN-13(EAN): 9783319626260
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Part I: Stochastic Chemical Reactions.- Test Models for Statistical Inference: Two-Dimensional Reaction Systems Displaying Limit Cycle Bifurcations and Bistability.- Importance Sampling for Metastable and Multiscale Dynamical Systems.- Multiscale Simulation of Stochastic Reaction-diffusion Networks.- Part II: Stochastic Numerical Approaches, Algorithms and Coarse-Grained Simulations.- Numerical Methods for Ergodic SDEs: When Stochastic Integration Meets Geometric Integration.- Stability and Strong Convergence for Spatial Stochastic Kinetics.- The T cells in an Ageing Virtual Mouse.- Part III: Analysis of Stochastic Dynamical Systems for Modeling Cell Biology.- Model reduction for Stochastic Reaction Systems.- ZI-closure Scheme: A Method to Solve and Study Stochastic Reaction Networks.- Deterministic and Stochastic Becker-Dцring Equations: Past and Recent Mathematical Developments.- Coagulation-Fragmentation with a Finite Number of Particles: Models, Stochastic Analysis and Applications to Telomere Clustering and Viral Capsid Assembly.- A Review of Stochastic and Delay Simulation Approaches in both Time and Space in Computational Cell Biology.- Part IV: Diffusion Processes and Stochastic Modeling.- Recent Mathematical Models of Axonal Transport.- Stochastic Models for Evolving Cellular Populations of Mitochondria: Disease, Development, and Ageing.- Modeling and Stochastic Analysis of the Single Photon Response.- A Phenomenological Spatial Model for Macro-ecological Patterns in Species-rich Ecosystems.

Evolution, Monitoring and Predicting Models of Rockburst

Автор: Wang
Название: Evolution, Monitoring and Predicting Models of Rockburst
ISBN: 9811075476 ISBN-13(EAN): 9789811075476
Издательство: Springer
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Цена: 6986.00 р.
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Описание:

Introduction.- Experimental Materials and Equipment.- The Mechanism and Predicting Theory-Based Rockburst Evolution.- Three-dimensional Reconstruction Model and Numerical Simulation of Rock Fissures.- The Patterns of Dynamic Evolution of Cracks in Rock Failure.- Experiment Investigation of AE Precursor Information for Rockburst.- Experimental Investigations on Multi-means and Synergistic Prediction for Rockburst.- Predicting Model of Rockburst Based on Nondeterministic Theory.- Field Case.

Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems: Using the Methods of Stochastic Processes

Автор: Rahimi Tabar M. Reza
Название: Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems: Using the Methods of Stochastic Processes
ISBN: 3030184749 ISBN-13(EAN): 9783030184742
Издательство: Springer
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Цена: 16070.00 р.
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Описание:
​1 Introduction.- 2 Introduction to Stochastic Processes.- 3 Kramers-Moyal Expansion and Fokker-Planck Equation.- 4 Continuous Stochastic Process.- 5 The Langevin Equation and Wiener Process.- 6 Stochastic Integration, It o and Stratonovich Calculi.- 7 Equivalence of Langevin and Fokker-Planck Equations.- 8 Examples of Stochastic Calculus.-9 Langevin Dynamics in Higher Dimensions.- 10 Levy Noise Driven Langevin Equation and its Time Series-Based Reconstruction.- 11 Stochastic Processes with Jumps and Non-Vanishing Higher-Order Kramers-Moyal Coefficients.- 12 Jump-Diffusion Processes.- 13 Two-Dimensional (Bivariate) Jump-Diffusion Processes.- 14 Numerical Solution of Stochastic Differential Equations: Diffusion and Jump-Diffusion Processes.- 15 The Friedrich-Peinke Approach to Reconstruction of Dynamical Equation for Time Series: Complexity in View of Stochastic Processes.- 16 How To Set Up Stochastic Equations For Real-World Processes: Markov-Einstein Time Scale.- 17 Reconstruction of Stochastic Dynamical Equations: Exemplary Stationary Diffusion and Jump-Diffusion Processes.- 18 The Kramers-Moyal Coefficients of Non-Stationary Time series in The Presence of Microstructure (Measurement) Noise.- 19 Influence of Finite Time Step in Estimating of the Kramers-Moyal Coefficients.- 20 Distinguishing Diffusive and Jumpy Behaviors in Real-World Time Series.- 21 Reconstruction of Langevin and Jump-Diffusion Dynamics From Empirical Uni- and Bivariate Time Series.- 22 Applications and Outlook.- 23 Epileptic Brain Dynamics.


Forecasting Innovations

Автор: Peter Hingley; Marc Nicolas
Название: Forecasting Innovations
ISBN: 3642071538 ISBN-13(EAN): 9783642071539
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This is a practical guide to solutions for forecasting demand for services and products in international markets - and much more than just a listing of dry theoretical methods. Leading experts present studies on improving methods for forecasting numbers of incoming patent filings at the European Patent Office.

Predicting Stock Returns

Автор: David G McMillan
Название: Predicting Stock Returns
ISBN: 3319690078 ISBN-13(EAN): 9783319690070
Издательство: Springer
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Цена: 7685.00 р.
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Описание: This book provides a comprehensive analysis of asset price movement. It examines different aspects of stock return predictability, the interaction between stock return and dividend growth predictability, the relationship between stocks and bonds, and the resulting implications for asset price movement.

Predicting the Future

Автор: Henry Abarbanel
Название: Predicting the Future
ISBN: 1461472172 ISBN-13(EAN): 9781461472179
Издательство: Springer
Рейтинг:
Цена: 14673.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book discusses model building and evaluation across disciplines, by means of an exact path integral for transferring information from observations to a model of the observed system. Offers examples in geosciences, nonlinear electrical circuits and more.

Predicting the Future

Автор: Henry Abarbanel
Название: Predicting the Future
ISBN: 1493952382 ISBN-13(EAN): 9781493952380
Издательство: Springer
Рейтинг:
Цена: 15672.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book discusses model building and evaluation across disciplines, by means of an exact path integral for transferring information from observations to a model of the observed system. Offers examples in geosciences, nonlinear electrical circuits and more.

The Helmholtz Equation Least Squares Method

Автор: Sean F. Wu
Название: The Helmholtz Equation Least Squares Method
ISBN: 1493916394 ISBN-13(EAN): 9781493916399
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
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Описание: This book represents the HELS (Helmholtz equation least squares) theory and its applications for visualizing acoustic radiation from an arbitrarily shaped vibrating structure in free or confined space. The first serves as a review of the fundamentals in acoustics and the rest cover five specific topics on the HELS theory.

Predicting the Impact of Patents

Автор: Hiroyasu Inoue
Название: Predicting the Impact of Patents
ISBN: 4431548068 ISBN-13(EAN): 9784431548065
Издательство: Springer
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Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This is the first book that comprehensively analyses co-patenting in Japan and the U.S., which directly signifies collaborations between firms and inventors, using the methodology of network science.


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