Deterministic And Stochastic Approaches In Computer Modeling And Simulation PDF Download
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Author | : Romansky, Radi Petrov |
Publisher | : IGI Global |
Total Pages | : 527 |
Release | : 2023-10-09 |
Genre | : Computers |
ISBN | : 166848949X |
Download Deterministic and Stochastic Approaches in Computer Modeling and Simulation Book in PDF, ePub and Kindle
In the field of computer modeling and simulation, academic scholars face a pressing challenge—how to navigate the complex landscape of both deterministic and stochastic approaches to modeling. This multifaceted arena demands a unified organizational framework, a comprehensive guide that can seamlessly bridge the gap between theory and practical application. Without such a resource, scholars may struggle to harness the full potential of computer modeling, leaving critical questions unanswered and innovative solutions undiscovered. Deterministic and Stochastic Approaches in Computer Modeling and Simulation serves as the definitive solution to the complex problem scholars encounter. By presenting a comprehensive and unified organizational approach, this book empowers academics to conquer the challenges of computer modeling with confidence. It not only provides a classification of modeling methods but also offers a formalized, step-by-step approach to conducting model investigations, starting from defining objectives to analyzing experimental results. For academic scholars seeking a holistic understanding of computer modeling, this book is the ultimate solution. It caters to the diverse needs of scholars by addressing both deterministic and stochastic approaches. Through its structured chapters, it guides readers from the very basics of computer systems investigation to advanced topics like stochastic analytical modeling and statistical modeling.
Author | : Radi Petrov Romansky |
Publisher | : |
Total Pages | : 0 |
Release | : 2023 |
Genre | : Computer simulation |
ISBN | : 9781668489482 |
Download Deterministic and Stochastic Approaches in Computer Modeling and Simulation Book in PDF, ePub and Kindle
"The purpose of this book is to make a summary of the possibilities of modeling research, mainly in the computer field, by discussing the areas of problems in mathematical formalization and abstract description, discrete and probabilistic modeling approaches, computer simulation and the empirical approach of statistical modeling"--
Author | : Paola Lecca |
Publisher | : Elsevier |
Total Pages | : 411 |
Release | : 2013-04-09 |
Genre | : Mathematics |
ISBN | : 1908818212 |
Download Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology Book in PDF, ePub and Kindle
Stochastic kinetic methods are currently considered to be the most realistic and elegant means of representing and simulating the dynamics of biochemical and biological networks. Deterministic versus stochastic modelling in biochemistry and systems biology introduces and critically reviews the deterministic and stochastic foundations of biochemical kinetics, covering applied stochastic process theory for application in the field of modelling and simulation of biological processes at the molecular scale. Following an overview of deterministic chemical kinetics and the stochastic approach to biochemical kinetics, the book goes onto discuss the specifics of stochastic simulation algorithms, modelling in systems biology and the structure of biochemical models. Later chapters cover reaction-diffusion systems, and provide an analysis of the Kinfer and BlenX software systems. The final chapter looks at simulation of ecodynamics and food web dynamics. Introduces mathematical concepts and formalisms of deterministic and stochastic modelling through clear and simple examples Presents recently developed discrete stochastic formalisms for modelling biological systems and processes Describes and applies stochastic simulation algorithms to implement a stochastic formulation of biochemical and biological kinetics
Author | : Hans-Joachim Bungartz |
Publisher | : Springer Science & Business Media |
Total Pages | : 415 |
Release | : 2013-10-24 |
Genre | : Computers |
ISBN | : 3642395244 |
Download Modeling and Simulation Book in PDF, ePub and Kindle
Die Autoren führen auf anschauliche und systematische Weise in die mathematische und informatische Modellierung sowie in die Simulation als universelle Methodik ein. Es geht um Klassen von Modellen und um die Vielfalt an Beschreibungsarten. Aber es geht immer auch darum, wie aus Modellen konkrete Simulationsergebnisse gewonnen werden können. Nach einem kompakten Repetitorium zum benötigten mathematischen Apparat wird das Konzept anhand von Szenarien u. a. aus den Bereichen „Spielen – entscheiden – planen" und „Physik im Rechner" umgesetzt.
Author | : D N Shanbhag |
Publisher | : Gulf Professional Publishing |
Total Pages | : 1028 |
Release | : 2003-02-24 |
Genre | : Mathematics |
ISBN | : 9780444500137 |
Download Stochastic Processes: Modeling and Simulation Book in PDF, ePub and Kindle
This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation is concerned mainly with the theme of reviewing and, in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value therapy, applications of Markov chains, modelling with Monte Carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the preface of volume 19. The present volume completes the aim of the project and should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes.
Author | : Ingels |
Publisher | : CRC Press |
Total Pages | : 180 |
Release | : 1985-10-02 |
Genre | : Computers |
ISBN | : 9780824774448 |
Download What Every Engineer Should Know about Computer Modeling and Simulation Book in PDF, ePub and Kindle
This book presents a brief description of what constitutes computer modeling and simulation with techniques given to get a feel for how some of the simulation software packages involving hundreds of thousands of lines of code were developed.
Author | : Dieter W. Heermann |
Publisher | : Springer Science & Business Media |
Total Pages | : 155 |
Release | : 2012-12-06 |
Genre | : Science |
ISBN | : 3642969712 |
Download Computer Simulation Methods in Theoretical Physics Book in PDF, ePub and Kindle
Appropriately for a book having the title "Computer Simulation Methods in Theoretical Physics", this book begins with a disclai mer. It does not and cannot give a complete introduction to simu lational physics. This exciting field is too new and is expanding too rapidly for even an attempt to be made. The intention here is to present a selection of fundamental techniques that are now being widely applied in many areas of physics, mathematics, chem istry and biology. It is worth noting that the methods are not only applicable in physics. They have been successfully used in other sciences, showing their great flexibility and power. This book has two main chapters (Chaps. 3 and 4) dealing with deterministic and stochastic computer simulation methods. Under the heading "deterministic" are collected methods involving classical dynamics, i.e. classical equations of motion, which have become known as the molecular dynamics simulation method. The se cond main chapter deals with methods that are partly or entirely of a stochastic nature. These include Brownian dynamics and the Monte Carlo method. To aid understanding of the material and to develop intuition, problems are included at the end of each chapter. Upon a first reading, the reader is advised to skip Chapter 2, which is a general introduction to computer simUlation methods.
Author | : Barry Nelson |
Publisher | : Springer Science & Business Media |
Total Pages | : 285 |
Release | : 2013-01-31 |
Genre | : Business & Economics |
ISBN | : 146146160X |
Download Foundations and Methods of Stochastic Simulation Book in PDF, ePub and Kindle
This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material); and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems and prepares the reader to use simulation in research as well as practice. The book is a rigorous, but concise treatment, emphasizing lasting principles but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research; no other book does this. An online solutions manual for end of chapter exercises is also provided.
Author | : Darren J. Wilkinson |
Publisher | : CRC Press |
Total Pages | : 296 |
Release | : 2006-04-18 |
Genre | : Mathematics |
ISBN | : 9781584885405 |
Download Stochastic Modelling for Systems Biology Book in PDF, ePub and Kindle
Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks, most researchers in the field have limited knowledge of stochastic process theory. The stochastic processes formalism provides a beautiful, elegant, and coherent foundation for chemical kinetics and there is a wealth of associated theory every bit as powerful and elegant as that for conventional continuous deterministic models. The time is right for an introductory text written from this perspective. Stochastic Modelling for Systems Biology presents an accessible introduction to stochastic modelling using examples that are familiar to systems biology researchers. Focusing on computer simulation, the author examines the use of stochastic processes for modelling biological systems. He provides a comprehensive understanding of stochastic kinetic modelling of biological networks in the systems biology context. The text covers the latest simulation techniques and research material, such as parameter inference, and includes many examples and figures as well as software code in R for various applications. While emphasizing the necessary probabilistic and stochastic methods, the author takes a practical approach, rooting his theoretical development in discussions of the intended application. Written with self-study in mind, the book includes technical chapters that deal with the difficult problems of inference for stochastic kinetic models from experimental data. Providing enough background information to make the subject accessible to the non-specialist, the book integrates a fairly diverse literature into a single convenient and notationally consistent source.
Author | : Dragan Poljak |
Publisher | : John Wiley & Sons |
Total Pages | : 580 |
Release | : 2023-11-17 |
Genre | : Science |
ISBN | : 1119989264 |
Download Deterministic and Stochastic Modeling in Computational Electromagnetics Book in PDF, ePub and Kindle
Deterministic and Stochastic Modeling in Computational Electromagnetics Help protect your network with this important reference work on cyber security Deterministic computational models are those for which all inputs are precisely known, whereas stochastic modeling reflects uncertainty or randomness in one or more of the data inputs. Many problems in computational engineering therefore require both deterministic and stochastic modeling to be used in parallel, allowing for different degrees of confidence and incorporating datasets of different kinds. In particular, non-intrusive stochastic methods can be easily combined with widely used deterministic approaches, enabling this more robust form of data analysis to be applied to a range of computational challenges. Deterministic and Stochastic Modeling in Computational Electromagnetics provides a rare treatment of parallel deterministic–stochastic computational modeling and its beneficial applications. Unlike other works of its kind, which generally treat deterministic and stochastic modeling in isolation from one another, it aims to demonstrate the usefulness of a combined approach and present particular use-cases in which such an approach is clearly required. It offers a non-intrusive stochastic approach which can be incorporated with minimal effort into virtually all existing computational models. Readers will also find: A range of specific examples demonstrating the efficiency of deterministic–stochastic modeling Computational examples of successful applications including ground penetrating radars (GPR), radiation from 5G systems, transcranial magnetic and electric stimulation (TMS and TES), and more Introduction to fundamental principles in field theory to ground the discussion of computational modeling Deterministic and Stochastic Modeling in Computational Electromagnetics is a valuable reference for researchers, including graduate and undergraduate students, in computational electromagnetics, as well as to multidisciplinary researchers, engineers, physicists, and mathematicians.