Minimization Of Computational Costs Of Non-analogue Monte Carlo Methods PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Minimization Of Computational Costs Of Non-analogue Monte Carlo Methods PDF full book. Access full book title Minimization Of Computational Costs Of Non-analogue Monte Carlo Methods by G A Mikhailov. Download full books in PDF and EPUB format.
Author: G A Mikhailov
Publisher: World Scientific
ISBN: 9814506117
Category : Mathematics
Languages : en
Pages : 173
Get Book Here
Book Description
Non-analogue Monte Carlo methods are useful when the direct simulation techniques are insufficient. To use the additional discretization, Monte Carlo estimates are biased and it is desirable to optimize the connection between discretization parameters and the sample size. In this connection, the book investigates variances of non-analogue Monte Carlo estimates, uniform minimization of variances by choosing a computational model and the minimization of computational cost of non-analogue Monte Carlo methods.This book is essentially new with respect to previous monographs on the Monte Carlo methods.
Author: G A Mikhailov
Publisher: World Scientific
ISBN: 9814506117
Category : Mathematics
Languages : en
Pages : 173
Get Book Here
Book Description
Non-analogue Monte Carlo methods are useful when the direct simulation techniques are insufficient. To use the additional discretization, Monte Carlo estimates are biased and it is desirable to optimize the connection between discretization parameters and the sample size. In this connection, the book investigates variances of non-analogue Monte Carlo estimates, uniform minimization of variances by choosing a computational model and the minimization of computational cost of non-analogue Monte Carlo methods.This book is essentially new with respect to previous monographs on the Monte Carlo methods.
Author: Emmanuel Gobet
Publisher: CRC Press
ISBN: 1498746233
Category : Mathematics
Languages : en
Pages : 310
Get Book Here
Book Description
Developed from the author’s course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear and nonlinear problems in biology, finance, geophysics, mechanics, chemistry, and other application areas. The text also thoroughly develops the problem of numerical integration and computation of expectation by the Monte-Carlo method. The book begins with a history of Monte-Carlo methods and an overview of three typical Monte-Carlo problems: numerical integration and computation of expectation, simulation of complex distributions, and stochastic optimization. The remainder of the text is organized in three parts of progressive difficulty. The first part presents basic tools for stochastic simulation and analysis of algorithm convergence. The second part describes Monte-Carlo methods for the simulation of stochastic differential equations. The final part discusses the simulation of non-linear dynamics.
Author: Oleg Mikhaĭlovich Belot︠s︡erkovskiĭ
Publisher: World Scientific
ISBN: 9814282367
Category : Mathematics
Languages : en
Pages : 281
Get Book Here
Book Description
This book is devoted to analysis of Monte Carlo methods developed in rarefied gas dynamics. Presented is the short history of the development of such methods, described are their main properties, their advantages and deficiencies. It is shown that the contemporary stage in the progress of computational methods cannot be regarded without a complex approach to the preparation of algorithms taking into account all the peculiarities of the problem under consideration, that is, of the physical nature of a process, the mathematical model and the theoretical aspects of computational mathematics and stochastic processes. Thoroughly investigated is the possibility of application of Monte Carlo methods in some kindred areas of science which are non-traditional for the use of statistical modeling (continuous media, turbulence). Considered are the possible directions of development of statistical modeling.
Author: Neal Noah Madras
Publisher: American Mathematical Soc.
ISBN: 0821819925
Category : Mathematics
Languages : en
Pages : 238
Get Book Here
Book Description
This volume contains the proceedings of the Workshop on Monte Carlo Methods held at The Fields Institute for Research in Mathematical Sciences (Toronto, 1998). The workshop brought together researchers in physics, statistics, and probability. The papers in this volume - of the invited speakers and contributors to the poster session - represent the interdisciplinary emphasis of the conference. Monte Carlo methods have been used intensively in many branches of scientific inquiry. Markov chain methods have been at the forefront of much of this work, serving as the basis of many numerical studies in statistical physics and related areas since the Metropolis algorithm was introduced in 1953. Statisticians and theoretical computer scientists have used these methods in recent years, working on different fundamental research questions, yet using similar Monte Carlo methodology. This volume focuses on Monte Carlo methods that appear to have wide applicability and emphasizes new methods, practical applications and theoretical analysis. It will be of interest to researchers and graduate students who study and/or use Monte Carlo methods in areas of probability, statistics, theoretical physics, or computer science.
Author: Arnaud Doucet
Publisher: Springer Science & Business Media
ISBN: 1475734379
Category : Mathematics
Languages : en
Pages : 590
Get Book Here
Book Description
Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.
Author: Malvin H. Kalos
Publisher: John Wiley & Sons
ISBN: 3527626220
Category : Science
Languages : en
Pages : 215
Get Book Here
Book Description
This introduction to Monte Carlo methods seeks to identify and study the unifying elements that underlie their effective application. Initial chapters provide a short treatment of the probability and statistics needed as background, enabling those without experience in Monte Carlo techniques to apply these ideas to their research. The book focuses on two basic themes: The first is the importance of random walks as they occur both in natural stochastic systems and in their relationship to integral and differential equations. The second theme is that of variance reduction in general and importance sampling in particular as a technique for efficient use of the methods. Random walks are introduced with an elementary example in which the modeling of radiation transport arises directly from a schematic probabilistic description of the interaction of radiation with matter. Building on this example, the relationship between random walks and integral equations is outlined. The applicability of these ideas to other problems is shown by a clear and elementary introduction to the solution of the Schrödinger equation by random walks. The text includes sample problems that readers can solve by themselves to illustrate the content of each chapter. This is the second, completely revised and extended edition of the successful monograph, which brings the treatment up to date and incorporates the many advances in Monte Carlo techniques and their applications, while retaining the original elementary but general approach.
Author: EL HAMI Abdelkhalak
Publisher: Lavoisier
ISBN: 2746295164
Category : Reliability (Engineering)
Languages : en
Pages : 396
Get Book Here
Book Description
La fiabilité des systèmes complexes est un défi majeur pour les entreprises industrielles. Ces dernières doivent répondre aux exigences des donneurs d’ordre dont le non-respect entraînerait des pénalités compromettant les marchés futurs. L’un des enjeux majeurs de l’optimisation fiabiliste est d’établir une surveillance rigoureuse, capable de prédire et de détecter les modes de défaillances des systèmes étudiés. Cet ouvrage présente les avancées de la recherche et de l’industrie appliquées aux domaines de l’optimisation, de la fiabilité et de la prise en compte des incertitudes en mécanique. Ce couplage est à la base de la compétitivité des entreprises dans les secteurs de l’automobile, de l’aéronautique, du génie civil ou encore de la défense. Accompagné d’exemples détaillés, Incertitudes, optimisation et fiabilité des structures présente les nouveaux outils de conception les plus performants. Il s’adresse aux ingénieurs et aux enseignants-chercheurs.
Author: Ivan Dimov
Publisher: World Scientific
ISBN: 9812779892
Category : Mathematics
Languages : en
Pages : 308
Get Book Here
Book Description
The Monte Carlo method is inherently parallel and the extensive and rapid development in parallel computers, computational clusters and grids has resulted in renewed and increasing interest in this method. At the same time there has been an expansion in the application areas and the method is now widely used in many important areas of science including nuclear and semiconductor physics, statistical mechanics and heat and mass transfer. This book attempts to bridge the gap between theory and practice concentrating on modern algorithmic implementation on parallel architecture machines. Although a suitable text for final year postgraduate mathematicians and computational scientists it is principally aimed at the applied scientists: only a small amount of mathematical knowledge is assumed and theorem proving is kept to a minimum, with the main focus being on parallel algorithms development often to applied industrial problems. A selection of algorithms developed both for serial and parallel machines are provided. Sample Chapter(s). Chapter 1: Introduction (231 KB). Contents: Basic Results of Monte Carlo Integration; Optimal Monte Carlo Method for Multidimensional Integrals of Smooth Functions; Iterative Monte Carlo Methods for Linear Equations; Markov Chain Monte Carlo Methods for Eigenvalue Problems; Monte Carlo Methods for Boundary-Value Problems (BVP); Superconvergent Monte Carlo for Density Function Simulation by B-Splines; Solving Non-Linear Equations; Algorithmic Effciency for Different Computer Models; Applications for Transport Modeling in Semiconductors and Nanowires. Readership: Applied scientists and mathematicians.
Author: Emmanuel Gobet
Publisher: Ecole Polytechnique
ISBN: 9782730216166
Category :
Languages : fr
Pages : 235
Get Book Here
Book Description
Author: Abdo Abou Jaoudé
Publisher: BoD – Books on Demand
ISBN: 1839687592
Category : Science
Languages : en
Pages : 234
Get Book Here
Book Description
In applied mathematics, the name Monte Carlo is given to the method of solving problems by means of experiments with random numbers. This name, after the casino at Monaco, was first applied around 1944 to the method of solving deterministic problems by reformulating them in terms of a problem with random elements, which could then be solved by large-scale sampling. But, by extension, the term has come to mean any simulation that uses random numbers. Monte Carlo methods have become among the most fundamental techniques of simulation in modern science. This book is an illustration of the use of Monte Carlo methods applied to solve specific problems in mathematics, engineering, physics, statistics, and science in general.
