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| Author | : K. M. Decker |
| Publisher | : |
| Total Pages | : 23 |
| Release | : 1990 |
| Genre | : |
| ISBN | : |
| Author | : Pooneh Saidi Bidokhti |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 189 |
| Release | : 2019-12-18 |
| Genre | : Computers |
| ISBN | : 1789855454 |
The Monte Carlo method is a numerical technique to model the probability of all possible outcomes in a process that cannot easily be predicted due to the interference of random variables. It is a technique used to understand the impact of risk, uncertainty, and ambiguity in forecasting models. However, this technique is complicated by the amount of computer time required to achieve sufficient precision in the simulations and evaluate their accuracy. This book discusses the general principles of the Monte Carlo method with an emphasis on techniques to decrease simulation time and increase accuracy.
| Author | : A. Dubi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 294 |
| Release | : 2000-01-21 |
| Genre | : Mathematics |
| ISBN | : |
Focusses on the industry and use of mathematical methods, in particular the Monte Carlo method as a tool that can support and improve the engineering of systems. The application of the Monte Carlo method to system engineering is a new concept and the Monte Carlo method allows serious mathematical treatment of real-world industrial systems. This book which includes a large number of worked examples from real industrial problems, will prove a valuable reference source for students, researchers and engineers. It presents a unified approach to time-dependent system behavior in which the Monte Carlo method serves as a tool to obtain solutions to real-world challenges. The author suggest that efficiency can be increased through this integrated approach which combines previously independent considerations such as product reliability, maintenance requirements and the availability of spare parts. Features include: * Comprehensive coverage of the basic theory behind systems engineering and the Monte Carlo method enabling the reader to understand the concepts involved * Description of the method from the basic estimation of simple statistical processes, through the evaluation of multidimensional integrals to the solution of complex transport equations * Extensive examples detailing practical industrial applications for each of the techniques presented * Accompanying software (available via ftp) relating to specific examples which allows the reader to use the methods described to solve practical problems * Discussion of a variety of analytical tools from classical probabilistic methods to the concepts of event distribution, aging and Markovian methods explaining how these fit into the general systems engineering framework.
| Author | : |
| Publisher | : |
| Total Pages | : |
| Release | : 19?? |
| Genre | : |
| ISBN | : 9789533076911 |
| Author | : Ronald W. Shonkwiler |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 249 |
| Release | : 2009-08-11 |
| Genre | : Mathematics |
| ISBN | : 0387878378 |
Monte Carlo methods are among the most used and useful computational tools available today, providing efficient and practical algorithims to solve a wide range of scientific and engineering problems. Applications covered in this book include optimization, finance, statistical mechanics, birth and death processes, and gambling systems. Explorations in Monte Carlo Methods provides a hands-on approach to learning this subject. Each new idea is carefully motivated by a realistic problem, thus leading from questions to theory via examples and numerical simulations. Programming exercises are integrated throughout the text as the primary vehicle for learning the material. Each chapter ends with a large collection of problems illustrating and directing the material. This book is suitable as a textbook for students of engineering and the sciences, as well as mathematics.
| Author | : Abdo Abou Jaoudé |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 234 |
| Release | : 2022-03-09 |
| Genre | : Science |
| ISBN | : 1839687592 |
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.
| Author | : George Fishman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 721 |
| Release | : 2013-03-09 |
| Genre | : Mathematics |
| ISBN | : 1475725531 |
Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.
| Author | : Wai Kin (Victor) Chan |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 288 |
| Release | : 2013-03-06 |
| Genre | : Computers |
| ISBN | : 9535110128 |
The purpose of this book is to introduce researchers and practitioners to recent advances and applications of Monte Carlo Simulation (MCS). Random sampling is the key of the MCS technique. The 11 chapters of this book collectively illustrates how such a sampling technique is exploited to solve difficult problems or analyze complex systems in various engineering and science domains. Issues related to the use of MCS including goodness-of-fit, uncertainty evaluation, variance reduction, optimization, and statistical estimation are discussed and examples of solutions are given. Novel applications of MCS are demonstrated in financial systems modeling, estimation of transition behavior of organic molecules, chemical reaction, particle diffusion, kinetic simulation of biophysics and biological data, and healthcare practices. To enlarge the accessibility of this book, both field-specific background materials and field-specific usages of MCS are introduced in most chapters. The aim of this book is to unify knowledge of MCS from different fields to facilitate research and new applications of MCS.
| Author | : Arnaud Doucet |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 590 |
| Release | : 2013-03-09 |
| Genre | : Mathematics |
| ISBN | : 1475734379 |
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 | : Dirk P. Kroese |
| Publisher | : John Wiley & Sons |
| Total Pages | : 627 |
| Release | : 2013-06-06 |
| Genre | : Mathematics |
| ISBN | : 1118014952 |
A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field. The authors begin with a discussion of fundamentals such as how to generate random numbers on a computer. Subsequent chapters discuss key Monte Carlo topics and methods, including: Random variable and stochastic process generation Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run Discrete-event simulation Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation Variance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo Estimation of derivatives and sensitivity analysis Advanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization The presented theoretical concepts are illustrated with worked examples that use MATLAB®, a related Web site houses the MATLAB® code, allowing readers to work hands-on with the material and also features the author's own lecture notes on Monte Carlo methods. Detailed appendices provide background material on probability theory, stochastic processes, and mathematical statistics as well as the key optimization concepts and techniques that are relevant to Monte Carlo simulation. Handbook of Monte Carlo Methods is an excellent reference for applied statisticians and practitioners working in the fields of engineering and finance who use or would like to learn how to use Monte Carlo in their research. It is also a suitable supplement for courses on Monte Carlo methods and computational statistics at the upper-undergraduate and graduate levels.
