Mathematica 9 is now available

Wolfram Library Archive


Courseware Demos MathSource Technical Notes
All Collections Articles Books Conference Proceedings
Title

Mathematical Modeling, Third Edition
Author

Mark M. Meerschaert
Book information

Publisher: Elsevier (Burlington, MA)
Copyright year: 2007
ISBN: 9780123708571
Medium: Hardcover
Pages: 334
Out of print?: N
Buy this book
Book cover image
Contents

I. Optimization Models
One-Variable Optimization | Multivariable Optimization | Computational Methods for Optimization
II. Dynamic Models
Introduction to Dynamic Models | Analysis of Dynamic Models | Simulation of Dynamic Models
III. Probability Models
Introduction to Probability Models | Stochastic Models | Simulation of Probability Models
Description

This book provides a general introduction to an increasingly crucial topic for today's mathematicians and covers a broad spectrum of modeling problems, from optimization to dynamical systems to stochastic processes. An emphasis on principles and general techniques offers students the mathematical background they need to model real-world problems in a wide range of disciplines.

Intended for advanced undergraduate or beginning graduate students in mathematics and closely related fields, knowledge of single and multivariable calculus, linear algebra, and differential equations is expected. Prior exposure to computing and probability and statistics is useful, but is not required.

This third edition is accompanied by expanded and enhanced online support for instructors. The text includes some computer output from Mathematica and complete Mathematica implementations of all of the algorithms in the book can be downloaded from the book's companion website. The programs are written in Mathematica 5.2 but are also compatible with Mathematica 6.0.
Subjects

*Applied Mathematics
*Applied Mathematics > Optimization
*Mathematics > Calculus and Analysis > Dynamical Systems
*Mathematics > Probability and Statistics
Keywords

Mathematical modeling, simulation, optimization, sensitivity analysis, dynamic models, dynamical systems, Markov Chains, Markov processes, time series, Monte Carlo, probability models, Euler method, chaos, fractals, statistics, docking problem, whale problem, tree problem, newspaper problem, state transition, multivariable optimization, diffusion
URL

http://www.stt.msu.edu/~mcubed/modeling.html