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Computational Mathematical Modeling: An Integrated Approach Across Scales

Computational Mathematical Modeling: An Integrated Approach Across Scales

Computational Mathematical Modeling: An Integrated Approach Across Scales

Daniela Calvetti, Case Western Reserve University, Ohio
Erkki Somersalo, Case Western Reserve University, Ohio
March 2013
Paperback
9781611972474
AUD$180.00
inc GST
Paperback

    Interesting real-world mathematical modeling problems are complex and can usually be studied at different scales. The scale at which the investigation is carried out is one of the factors that determines the type of mathematics most appropriate to describe the problem. The book concentrates on two modeling paradigms: the macroscopic, in which phenomena are described in terms of time evolution via ordinary differential equations; and the microscopic, which requires knowledge of random events and probability. The exposition is based on this unorthodox combination of deterministic and probabilistic methodologies, and emphasizes the development of computational skills to construct predictive models. To elucidate the concepts, a wealth of examples, self-study problems, and portions of MATLAB code used by the authors are included. This book, which has been extensively tested by the authors for classroom use, is intended for students in mathematics and the physical sciences at the advanced undergraduate level and above.

    • Features an unorthodox combination of macroscopic and microscopic methodologies
    • Designed for classroom use and features plenty of instructive examples and exercises
    • Provides a painless introduction to advanced themes and emphasises the development of computational skills

    Product details

    March 2013
    Paperback
    9781611972474
    234 pages
    254 × 178 × 12 mm
    0.44kg
    This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.

    Table of Contents

    • Preface
    • 1. Review of multivariate calculus and differential equations
    • 2. Compartment models
    • 3. From compartment models to continuous models
    • 4. Dimensional analysis and scaling
    • 5. Introduction to stochastic modeling
    • 6. Modeling of noise
    • 7. Modeling with waiting processes
    • 8. Markov processes
    • 9. Cellular automata, agent-based modeling
    • Bibliography
    • Index.