Download or read book Process Analysis and Simulation Deterministic Systems written by David Mautner Himmelblau and published by . This book was released on 1980 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Simulations with deterministic processes written by Harvey Gould and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology written by Paola Lecca and published by Elsevier. This book was released on 2013-04-09 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Process Analysis and Simulation written by David Mautner Himmelblau and published by . This book was released on 1975 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deterministic Simulation of Random Processes written by Joel N. Franklin and published by . This book was released on 1962 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Numerical Methods for Simulation and Optimization of Piecewise Deterministic Markov Processes written by Benoîte de Saporta and published by John Wiley & Sons. This book was released on 2016-01-26 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mark H.A. Davis introduced the Piecewise-Deterministic Markov Process (PDMP) class of stochastic hybrid models in an article in 1984. Today it is used to model a variety of complex systems in the fields of engineering, economics, management sciences, biology, Internet traffic, networks and many more. Yet, despite this, there is very little in the way of literature devoted to the development of numerical methods for PDMDs to solve problems of practical importance, or the computational control of PDMPs. This book therefore presents a collection of mathematical tools that have been recently developed to tackle such problems. It begins by doing so through examples in several application domains such as reliability. The second part is devoted to the study and simulation of expectations of functionals of PDMPs. Finally, the third part introduces the development of numerical techniques for optimal control problems such as stopping and impulse control problems.
Download or read book Markov Renewal and Piecewise Deterministic Processes written by Christiane Cocozza-Thivent and published by Springer Nature. This book was released on 2021-06-09 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at researchers, graduate students and engineers who would like to be initiated to Piecewise Deterministic Markov Processes (PDMPs). A PDMP models a deterministic mechanism modified by jumps that occur at random times. The fields of applications are numerous : insurance and risk, biology, communication networks, dependability, supply management, etc. Indeed, the PDMPs studied so far are in fact deterministic functions of CSMPs (Completed Semi-Markov Processes), i.e. semi-Markov processes completed to become Markov processes. This remark leads to considerably broaden the definition of PDMPs and allows their properties to be deduced from those of CSMPs, which are easier to grasp. Stability is studied within a very general framework. In the other chapters, the results become more accurate as the assumptions become more precise. Generalized Chapman-Kolmogorov equations lead to numerical schemes. The last chapter is an opening on processes for which the deterministic flow of the PDMP is replaced with a Markov process. Marked point processes play a key role throughout this book.
Download or read book Stochastic Processes Modeling and Simulation written by D N Shanbhag and published by Gulf Professional Publishing. This book was released on 2003-02-24 with total page 1028 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Molecular Dynamics written by Ben Leimkuhler and published by Springer. This book was released on 2015-05-18 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the mathematical underpinnings of algorithms used for molecular dynamics simulation, including both deterministic and stochastic numerical methods. Molecular dynamics is one of the most versatile and powerful methods of modern computational science and engineering and is used widely in chemistry, physics, materials science and biology. Understanding the foundations of numerical methods means knowing how to select the best one for a given problem (from the wide range of techniques on offer) and how to create new, efficient methods to address particular challenges as they arise in complex applications. Aimed at a broad audience, this book presents the basic theory of Hamiltonian mechanics and stochastic differential equations, as well as topics including symplectic numerical methods, the handling of constraints and rigid bodies, the efficient treatment of Langevin dynamics, thermostats to control the molecular ensemble, multiple time-stepping, and the dissipative particle dynamics method.
Download or read book Stochastic Population Processes written by Eric Renshaw and published by Oxford University Press. This book was released on 2015 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: A reference text presenting stochastic processes and a range of approximation and simulation techniques for extracting behavioural information in the context of stochastic population dynamics.
Download or read book Deterministic and Stochastic Optimal Control written by Wendell H. Fleming and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book may be regarded as consisting of two parts. In Chapters I-IV we pre sent what we regard as essential topics in an introduction to deterministic optimal control theory. This material has been used by the authors for one semester graduate-level courses at Brown University and the University of Kentucky. The simplest problem in calculus of variations is taken as the point of departure, in Chapter I. Chapters II, III, and IV deal with necessary conditions for an opti mum, existence and regularity theorems for optimal controls, and the method of dynamic programming. The beginning reader may find it useful first to learn the main results, corollaries, and examples. These tend to be found in the earlier parts of each chapter. We have deliberately postponed some difficult technical proofs to later parts of these chapters. In the second part of the book we give an introduction to stochastic optimal control for Markov diffusion processes. Our treatment follows the dynamic pro gramming method, and depends on the intimate relationship between second order partial differential equations of parabolic type and stochastic differential equations. This relationship is reviewed in Chapter V, which may be read inde pendently of Chapters I-IV. Chapter VI is based to a considerable extent on the authors' work in stochastic control since 1961. It also includes two other topics important for applications, namely, the solution to the stochastic linear regulator and the separation principle.
Download or read book Mathematical Modeling of Random and Deterministic Phenomena written by Solym Mawaki Manou-Abi and published by John Wiley & Sons. This book was released on 2020-04-28 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights mathematical research interests that appear in real life, such as the study and modeling of random and deterministic phenomena. As such, it provides current research in mathematics, with applications in biological and environmental sciences, ecology, epidemiology and social perspectives. The chapters can be read independently of each other, with dedicated references specific to each chapter. The book is organized in two main parts. The first is devoted to some advanced mathematical problems regarding epidemic models; predictions of biomass; space-time modeling of extreme rainfall; modeling with the piecewise deterministic Markov process; optimal control problems; evolution equations in a periodic environment; and the analysis of the heat equation. The second is devoted to a modelization with interdisciplinarity in ecological, socio-economic, epistemological, demographic and social problems. Mathematical Modeling of Random and Deterministic Phenomena is aimed at expert readers, young researchers, plus graduate and advanced undergraduate students who are interested in probability, statistics, modeling and mathematical analysis.
Download or read book Stochastic Modelling of Reaction Diffusion Processes written by Radek Erban and published by Cambridge University Press. This book was released on 2020-01-30 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical introduction to stochastic reaction-diffusion modelling is based on courses taught at the University of Oxford. The authors discuss the essence of mathematical methods which appear (under different names) in a number of interdisciplinary scientific fields bridging mathematics and computations with biology and chemistry. The book can be used both for self-study and as a supporting text for advanced undergraduate or beginning graduate-level courses in applied mathematics. New mathematical approaches are explained using simple examples of biological models, which range in size from simulations of small biomolecules to groups of animals. The book starts with stochastic modelling of chemical reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio-temporal models are then studied, including models of diffusion and stochastic reaction-diffusion modelling. The methods covered include molecular dynamics, Brownian dynamics, velocity jump processes and compartment-based (lattice-based) models.
Download or read book Stochastic Simulation and Monte Carlo Methods written by Carl Graham and published by Springer Science & Business Media. This book was released on 2013-07-16 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners’ aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations.
Download or read book Deterministic Operations Research written by David J. Rader and published by John Wiley & Sons. This book was released on 2013-06-07 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations research: modeling real-world problems as linear optimization problem; designing the necessary algorithms to solve these problems; and using mathematical theory to justify algorithmic development. Treating real-world examples as mathematical problems, the author begins with an introduction to operations research and optimization modeling that includes applications form sports scheduling an the airline industry. Subsequent chapters discuss algorithm design for continuous linear optimization problems, covering topics such as convexity. Farkas’ Lemma, and the study of polyhedral before culminating in a discussion of the Simplex Method. The book also addresses linear programming duality theory and its use in algorithm design as well as the Dual Simplex Method. Dantzig-Wolfe decomposition, and a primal-dual interior point algorithm. The final chapters present network optimization and integer programming problems, highlighting various specialized topics including label-correcting algorithms for the shortest path problem, preprocessing and probing in integer programming, lifting of valid inequalities, and branch and cut algorithms. Concepts and approaches are introduced by outlining examples that demonstrate and motivate theoretical concepts. The accessible presentation of advanced ideas makes core aspects easy to understand and encourages readers to understand how to think about the problem, not just what to think. Relevant historical summaries can be found throughout the book, and each chapter is designed as the continuation of the “story” of how to both model and solve optimization problems by using the specific problems-linear and integer programs-as guides. The book’s various examples are accompanied by the appropriate models and calculations, and a related Web site features these models along with MapleTM and MATLAB® content for the discussed calculations. Thoroughly class-tested to ensure a straightforward, hands-on approach, Deterministic Operations Research is an excellent book for operations research of linear optimization courses at the upper-undergraduate and graduate levels. It also serves as an insightful reference for individuals working in the fields of mathematics, engineering, computer science, and operations research who use and design algorithms to solve problem in their everyday work.
Download or read book Random Processes Measurement Analysis and Simulation written by J. Cacko and published by Elsevier. This book was released on 2012-12-02 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the basic topics associated with the measurement, analysis and simulation of random environmental processes which are encountered in practice when dealing with the dynamics, fatigue and reliability of structures in real environmental conditions. The treatment is self-contained and the authors have brought together and integrated the most important information relevant to this topic in order that the newcomer can see and study it as a whole. This approach should also be of interest to experienced engineers from fatigue laboratories who want to learn more about the possible methods of simulation, especially for use in real time on electrohydraulic computer-controlled loading machines.Problems of constructing a measuring system are dealt with in the first chapter. Here the authors discuss the choice of measuring conditions and locations, as well as the organization of a chain of devices for measuring and recording random environmental processes. Some experience gained from practical measurements is also presented. The recorded processes are further analysed by various methods. The choice is governed by the aims of the measurements and applications of the results. Chapter 2 is thus devoted to methods of random process evaluations for digital computers, both from the fatigue and dynamic point of view. The most important chapter is Chapter 3 as this presents a review of up-to-date methods of random process simulation with given statistical characteristics. These methods naturally follow those of random process analysis, and their results form initial data for the corresponding simulations algorithms, including occurrences of characteristic parameters of counting methods, reproduction of correlation theory characteristics and of autoregressive models. The simulation of non-stationary processes is treated in depth, taking into account their importance for practical applications and also the lack of information of this subject.The book is intended to help resolve many practical problems concerning the methods and quality of environmental process evaluation and simulation which can arise when up-to-date loading systems with computer control are being used in material, component and structural fatigue and dynamic research.
Download or read book Deterministic and Stochastic Approaches in Computer Modeling and Simulation written by Romansky, Radi Petrov and published by IGI Global. This book was released on 2023-10-09 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
