1st Edition
by Xin-She Yang (Editor)
Features mathematical modeling techniques and real-world processes with applications in diverse fields
Mathematical Modeling with Multidisciplinary Applications
details the interdisciplinary nature of mathematical modeling and
numerical algorithms. The book combines a variety of applications from
diverse fields to illustrate how the methods can be used to model
physical processes, design new products, find solutions to challenging
problems, and increase competitiveness in international markets.
Written
by leading scholars and international experts in the field, the book
presents new and emerging topics in areas including finance and
economics, theoretical and applied mathematics, engineering and machine
learning, physics, chemistry, ecology, and social science. In addition,
the book thoroughly summarizes widely used mathematical and numerical
methods in mathematical modeling and features:
- Diverse
topics such as partial differential equations (PDEs), fractional
calculus, inverse problems by ordinary differential equations (ODEs),
semigroups, decision theory, risk analysis, Bayesian estimation,
nonlinear PDEs in financial engineering, perturbation analysis, and
dynamic system modeling
- Case studies and real-world
applications that are widely used for current mathematical modeling
courses, such as the green house effect and Stokes flow estimation
- Comprehensive
coverage of a wide range of contemporary topics, such as game theory,
statistical models, and analytical solutions to numerical methods
- Examples, exercises with select solutions, and detailed references to the latest literature to solidify comprehensive learning
- New techniques and applications with balanced coverage of PDEs, discrete models, statistics, fractional calculus, and more
Mathematical Modeling with Multidisciplinary Applications is
an excellent book for courses on mathematical modeling and applied
mathematics at the upper-undergraduate and graduate levels. The book
also serves as a valuable reference for research scientists,
mathematicians, and engineers who would like to develop further insights
into essential mathematical tools.