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From genetic engineering to hurricane prediction, mathematical models increasingly guide much of the decision-making in our world. If the assumptions and methods underlying the mo… Read more
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From genetic engineering to hurricane prediction, mathematical models increasingly guide much of the decision-making in our world. If the assumptions and methods underlying the modeling are flawed, the outcome can be disastrously poor. With mathematical modeling growing rapidly in many scientific and technical disciplines, Mathematical Modeling provides reliable overviews of major modeling techniques to guide quality application in appropriate settings.
Now in its Fifth Edition, Mathematical Modeling offers a trusted survey for mathematical modeling courses, with online instructor support and updated problems. This valued text explores a range of approaches, including optimization models, dynamic models, and probability models. Each module begins with a real-world problem, followed by a discussion of techniques, solving the problem using the described technique, and interpretation of the results. Through this practical and clear coverage,
Features sections on time series analysis and diffusion models
Includes additional problems on real world applications and optimization problems
Offers instructor support material, including MATLAB material
Primary market/audience (and market size, if known)
:
Students (~4,000-4,500 students/year, in 4-year colleges tracked by NavStem) at the advanced undergraduate / early graduate level
Secondary market/audience:
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Researchers/Professionals
I. OPTIMIZATION MODELS 1. One-Variable Optimization 2. Multivariable Optimization 3. Computational Methods for Optimization II. DYNAMIC MODELS Chapter 4. Introduction to Dynamic Models Chapter 5. Analysis of Dynamic Models Chapter 6. Simulation of Dynamic Models III. PROBABILITY MODELS 7. Introduction to Probability Models 8. Stochastic Models 9. Simulation of Probability Models
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