Stochastic Methods For Modeling And Predicting Complex Dynamical Systems

Author : Nan Chen
Publisher : Springer Nature
Page : 208 pages
File Size : 40,6 Mb
Release : 2023-03-13
Category : Mathematics
ISBN : 9783031222498

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Stochastic Methods for Modeling and Predicting Complex Dynamical Systems by Nan Chen Pdf

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.

Author : Yurii A. Kravtsov,James B. Kadtke
Publisher : Springer
Page : 234 pages
File Size : 55,9 Mb
Release : 2012-01-06
Category : Science
ISBN : 3642802559

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Predictability of Complex Dynamical Systems by Yurii A. Kravtsov,James B. Kadtke Pdf

Author : Howard M. Taylor,Samuel Karlin
Publisher : Academic Press
Page : 410 pages
File Size : 50,8 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483269276

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An Introduction to Stochastic Modeling by Howard M. Taylor,Samuel Karlin Pdf

An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Author : Stefan Heinz,Hakima Bessaih
Publisher : Springer
Page : 192 pages
File Size : 44,6 Mb
Release : 2015-05-06
Category : Mathematics
ISBN : 9783319182063

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Stochastic Equations for Complex Systems by Stefan Heinz,Hakima Bessaih Pdf

Mathematical analyses and computational predictions of the behavior of complex systems are needed to effectively deal with weather and climate predictions, for example, and the optimal design of technical processes. Given the random nature of such systems and the recognized relevance of randomness, the equations used to describe such systems usually need to involve stochastics. The basic goal of this book is to introduce the mathematics and application of stochastic equations used for the modeling of complex systems. A first focus is on the introduction to different topics in mathematical analysis. A second focus is on the application of mathematical tools to the analysis of stochastic equations. A third focus is on the development and application of stochastic methods to simulate turbulent flows as seen in reality. This book is primarily oriented towards mathematics and engineering PhD students, young and experienced researchers, and professionals working in the area of stochastic differential equations and their applications. It contributes to a growing understanding of concepts and terminology used by mathematicians, engineers, and physicists in this relatively young and quickly expanding field.

Author : V. G. Kulkarni
Publisher : Springer
Page : 313 pages
File Size : 40,6 Mb
Release : 2010-11-03
Category : Mathematics
ISBN : 9781441917720

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Introduction to Modeling and Analysis of Stochastic Systems by V. G. Kulkarni Pdf

This book provides a self-contained review of all the relevant topics in probability theory. A software package called MAXIM, which runs on MATLAB, is made available for downloading. Vidyadhar G. Kulkarni is Professor of Operations Research at the University of North Carolina at Chapel Hill.

Author : M. H. A. Davis,Richard B. Vinter
Publisher : Springer
Page : 416 pages
File Size : 47,9 Mb
Release : 1985
Category : Juvenile Nonfiction
ISBN : UCAL:B5008624

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Stochastic Modelling and Control by M. H. A. Davis,Richard B. Vinter Pdf

This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory.

Author : James B. Kadtke
Publisher : Springer
Page : 256 pages
File Size : 52,5 Mb
Release : 1996-10-04
Category : Business & Economics
ISBN : UOM:39015038181429

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Predictability of Complex Dynamical Systems by James B. Kadtke Pdf

This practical guide to data analysis and algorithms addresses researchers and practitioners interested in modeling, prediction, and forecasting natural systems based on nonlinear dynamics. It explores many interesting topics in complex dynamical systems and shows how probabilistic techniques, such as signal and time-series analysis, financial and stochastic modeling, and political modeling can be used to predict them.

Author : Christos H Skiadas
Publisher : World Scientific
Page : 668 pages
File Size : 50,8 Mb
Release : 2007-11-16
Category : Mathematics
ISBN : 9789814474474

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Recent Advances In Stochastic Modeling And Data Analysis by Christos H Skiadas Pdf

This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics.

Author : Paolo Sibani,Henrik Jeldtoft Jensen
Publisher : World Scientific Publishing Company
Page : 300 pages
File Size : 44,7 Mb
Release : 2013-02-20
Category : Mathematics
ISBN : 9781848169951

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Stochastic Dynamics of Complex Systems by Paolo Sibani,Henrik Jeldtoft Jensen Pdf

Dynamical evolution over long time scales is a prominent feature of all the systems we intuitively think of as complex — for example, ecosystems, the brain or the economy. In physics, the term ageing is used for this type of slow change, occurring over time scales much longer than the patience, or indeed the lifetime, of the observer. The main focus of this book is on the stochastic processes which cause ageing, and the surprising fact that the ageing dynamics of systems which are very different at the microscopic level can be treated in similar ways. The first part of this book provides the necessary mathematical and computational tools and the second part describes the intuition needed to deal with these systems. Some of the first few chapters have been covered in several other books, but the emphasis and selection of the topics reflect both the authors' interests and the overall theme of the book. The second part contains an introduction to the scientific literature and deals in some detail with the description of complex phenomena of a physical and biological nature, for example, disordered magnetic materials, superconductors and glasses, models of co-evolution in ecosystems and even of ant behaviour. These heterogeneous topics are all dealt with in detail using similar analytical techniques. This book emphasizes the unity of complex dynamics and provides the tools needed to treat a large number of complex systems of current interest. The ideas and the approach to complex dynamics it presents have not appeared in book form until now.

Author : Toshio Nakagawa
Publisher : Springer Science & Business Media
Page : 254 pages
File Size : 49,9 Mb
Release : 2011-05-27
Category : Technology & Engineering
ISBN : 9780857292742

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Stochastic Processes by Toshio Nakagawa Pdf

Reliability theory is of fundamental importance for engineers and managers involved in the manufacture of high-quality products and the design of reliable systems. In order to make sense of the theory, however, and to apply it to real systems, an understanding of the basic stochastic processes is indispensable. As well as providing readers with useful reliability studies and applications, Stochastic Processes also gives a basic treatment of such stochastic processes as: the Poisson process, the renewal process, the Markov chain, the Markov process, and the Markov renewal process. Many examples are cited from reliability models to show the reader how to apply stochastic processes. Furthermore, Stochastic Processes gives a simple introduction to other stochastic processes such as the cumulative process, the Wiener process, the Brownian motion and reliability applications. Stochastic Processes is suitable for use as a reliability textbook by advanced undergraduate and graduate students. It is also of interest to researchers, engineers and managers who study or practise reliability and maintenance.

Author : Taylor & Francis Group
Publisher : Unknown
Page : 128 pages
File Size : 42,5 Mb
Release : 2009-12-11
Category : Electronic
ISBN : 1439835381

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Modeling and Analysis of Stochastic Systems Second Edition - Solutions Manual by Taylor & Francis Group Pdf

This practical and accessible text enables readers from engineering, business, operations research, public policy and computer science to analyze stochastic systems. Emphasizing the modeling of real-life situations with stochastic elements and analyzing the resulting stochastic model, it presents the major cases of useful stochastic processes-discrete and continuous time Markov chains, renewal processes, regenerative processes, and Markov regenerative processes. The author provides reader-friendly yet rigorous coverage. He follows a set pattern of development for each class of stochastic processes and introduces Markov chains before renewal processes, so that readers can begin modeling systems early. He demonstrates both numerical and analytical solution methods in detail and dedicates a separate chapter to queueing applications. Modeling and Analysis of Stochastic Systems includes numerous worked examples and exercises, conveniently categorized as modeling, computational, or conceptual and making difficult concepts easy to grasp. Taking a practical approach to working with stochastic models, this book helps readers to model and analyze the increasingly complex and interdependent systems made possible by recent advances.

Author : Foster Morrison
Publisher : Courier Corporation
Page : 418 pages
File Size : 42,8 Mb
Release : 2012-03-07
Category : Mathematics
ISBN : 9780486131719

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The Art of Modeling Dynamic Systems by Foster Morrison Pdf

This text illustrates the roles of statistical methods, coordinate transformations, and mathematical analysis in mapping complex, unpredictable dynamical systems. It describes the benefits and limitations of the available modeling tools, showing engineers and scientists how any system can be rendered simpler and more predictable. Written by a well-known authority in the field, this volume employs practical examples and analogies to make models more meaningful. The more universal methods appear in considerable detail, and advanced dynamic principles feature easy-to-understand examples. The text draws careful distinctions between mathematical abstractions and observable realities. Additional topics include the role of pure mathematics, the limitations of numerical methods, forecasting in the presence of chaos and randomness, and dynamics without calculus. Specialized techniques and case histories are coordinated with a carefully selected and annotated bibliography. The original edition was a Library of Science Main Selection in May, 1991. This new Dover edition features corrections by the author and a new Preface.

Author : John A. Borrie
Publisher : Unknown
Page : 308 pages
File Size : 43,6 Mb
Release : 1992
Category : Mathematics
ISBN : STANFORD:36105024151974

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Stochastic Systems for Engineers by John A. Borrie Pdf

A self-contained introduction to stochastic systems and an ordered presentation of techniques for computer modelling, filtering and control of these systems. The subject is developed with definition, formulae and explanations but without detailed mathematical proofs.

Author : Mariano J Valderrama Bonnet,Ramon Gutierrez
Publisher : World Scientific
Page : 326 pages
File Size : 55,5 Mb
Release : 1994-09-30
Category : Electronic
ISBN : 9789814550703

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Selected Topics On Stochastic Modelling by Mariano J Valderrama Bonnet,Ramon Gutierrez Pdf

This volume contains a selection of papers on recent developments in fields such as stochastic processes, multivariate data analysis and stochastic models in operations research, earth and life sciences and information theory, from an applicative perspective. Some of them have been extracted from lectures given at the Department of Statistics and Operations Research at the University of Granada for the past two years (Kai Lai Chung and Marcel F Neuts, among others). All the papers have been carefully selected and revised.

Author : Yurii A. Kravtsov,James B. Kadtke
Publisher : Springer Science & Business Media
Page : 233 pages
File Size : 41,8 Mb
Release : 2012-12-06
Category : Science
ISBN : 9783642802546

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Predictability of Complex Dynamical Systems by Yurii A. Kravtsov,James B. Kadtke Pdf

This is a book book for researchers and practitioners interested in modeling, prediction and forecasting of natural systems based on nonlinear dynamics. It is a practical guide to data analysis and to the development of algorithms, especially for complex systems. Topics such as the characterization of nonlinear correlations in data as dynamical systems, reconstruction of dynamical models from data, nonlinear noise reduction and the limits of predicatability are discussed. The chapters are written by leading experts and consider practical problems such as signal and time series analysis, biomedical data analysis, financial analysis, stochastic modeling, human evolution, and political modeling. The book includes new methods for nonlinear filtering of complex signals, new algorithms for signal classification, and the concept of the "Global Brain".