Computer Simulation, Osais

Автор: Xue
Название: System Simulation Techniques with MATLAB and Simulink
ISBN: 1118647920 ISBN-13(EAN): 9781118647929
Издательство: Wiley
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Цена: 94990.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: System Simulation Techniques with MATLAB and Simulink comprehensively explains how to use MATLAB and Simulink to perform dynamic systems simulation tasks for engineering and non-engineering applications.

Автор: Gordon
Название: Introduction to Modeling and Simulation with MATLAB and Python
ISBN: 1498773877 ISBN-13(EAN): 9781498773874
Издательство: Taylor&Francis
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Цена: 89820.00 T
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Описание: The book introduces the principles of mathematical modeling in science, engineering, and social science as well as basic skills of computer programming. The book is aimed at majors in STEM disciplines that need to understand how to create, analyze, and test mathematical models.

Автор: Asmussen
Название: Stochastic Simulation: Algorithms and Analysis
ISBN: 038730679X ISBN-13(EAN): 9780387306797
Издательство: Springer
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Цена: 46540.00 T
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Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first  half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of  examples, exercises and applications students, practitioners and researchers in  probability, statistics, operations research, economics, finance, engineering  as well as biology and chemistry and physics will find the book of value.  Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of  Engineering at Stanford University. 

Автор: Lytton William W.
Название: From Computer to Brain / Foundations of Computational Neuroscience
ISBN: 0387955267 ISBN-13(EAN): 9780387955261
Издательство: Springer
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Цена: 41880.00 T
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Описание: Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.

Автор: Brandimarte P
Название: Handbook in Monte Carlo Simulation
ISBN: 0470531118 ISBN-13(EAN): 9780470531112
Издательство: Wiley
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Цена: 136170.00 T
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Описание: Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applications of Monte Carlo methods in financial engineering and economics.

Автор: Chen Chun-Hung, Jia Qing-Shan, Lee Loo Hay
Название: Stochastic Simulation Optimization for Discrete Event Systems: Perturbation Analysis, Ordinal Optimization and Beyond
ISBN: 9814513008 ISBN-13(EAN): 9789814513005
Издательство: World Scientific Publishing
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Цена: 85530.00 T
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Описание: Discrete event systems (DES) have become pervasive in our daily lives. Examples include (but are not restricted to) manufacturing and supply chains, transportation, healthcare, call centers, and financial engineering. However, due to their complexities that often involve millions or even billions of events with many variables and constraints, modeling these stochastic simulations has long been a "hard nut to crack." The advance in available computer technology, especially of cluster and cloud computing, has paved the way for the realization of a number of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and developed by Professor Y C Ho and his team; namely perturbation analysis and ordinal optimization for stochastic simulation optimization, and present the state-of-the-art technology, and their future research directions.