Stochastic Methods For Modeling And Predicting Complex Dynamical Systems
DOWNLOAD
FREE 30 Days
Download Stochastic Methods For Modeling And Predicting Complex Dynamical Systems PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Stochastic Methods For Modeling And Predicting Complex Dynamical Systems book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Stochastic Methods For Modeling And Predicting Complex Dynamical Systems
DOWNLOAD
FREE 30 Days
Author : Nan Chen
language : en
Publisher: Springer Nature
Release Date : 2023-03-13
Stochastic Methods For Modeling And Predicting Complex Dynamical Systems written by Nan Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-13 with Mathematics categories.
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.
Predictability Of Complex Dynamical Systems
DOWNLOAD
FREE 30 Days
Author : Yurii A. Kravtsov
language : en
Publisher: Springer
Release Date : 2012-01-06
Predictability Of Complex Dynamical Systems written by Yurii A. Kravtsov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-06 with Science categories.
Predictability Of Complex Dynamical Systems
DOWNLOAD
FREE 30 Days
Author : James B. Kadtke
language : en
Publisher: Springer
Release Date : 1996-10-04
Predictability Of Complex Dynamical Systems written by James B. Kadtke and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-10-04 with Business & Economics categories.
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.
An Introduction To Stochastic Modeling
DOWNLOAD
FREE 30 Days
Author : Howard M. Taylor
language : en
Publisher: Academic Press
Release Date : 2014-05-10
An Introduction To Stochastic Modeling written by Howard M. Taylor and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Mathematics categories.
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.
Stochastic Equations For Complex Systems
DOWNLOAD
FREE 30 Days
Author : Stefan Heinz
language : en
Publisher: Springer
Release Date : 2015-05-06
Stochastic Equations For Complex Systems written by Stefan Heinz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-06 with Mathematics categories.
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.
Introduction To Modeling And Analysis Of Stochastic Systems
DOWNLOAD
FREE 30 Days
Author : V. G. Kulkarni
language : en
Publisher: Springer
Release Date : 2010-11-03
Introduction To Modeling And Analysis Of Stochastic Systems written by V. G. Kulkarni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-03 with Mathematics categories.
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.
Stochastic Modelling And Control
DOWNLOAD
FREE 30 Days
Author : M. H. A. Davis
language : en
Publisher: Springer
Release Date : 1985
Stochastic Modelling And Control written by M. H. A. Davis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Juvenile Nonfiction categories.
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.
Modeling And Analysis Of Stochastic Systems Second Edition Solutions Manual
DOWNLOAD
FREE 30 Days
Author : Taylor & Francis Group
language : en
Publisher:
Release Date : 2009-12-11
Modeling And Analysis Of Stochastic Systems Second Edition Solutions Manual written by Taylor & Francis Group and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-11 with categories.
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.
Recent Advances In Stochastic Modeling And Data Analysis
DOWNLOAD
FREE 30 Days
Author : Christos H Skiadas
language : en
Publisher: World Scientific
Release Date : 2007-11-16
Recent Advances In Stochastic Modeling And Data Analysis written by Christos H Skiadas and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-16 with Mathematics categories.
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.
Stochastic Systems For Engineers
DOWNLOAD
FREE 30 Days
Author : John A. Borrie
language : en
Publisher:
Release Date : 1992
Stochastic Systems For Engineers written by John A. Borrie and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Mathematics categories.
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.