Mathematical Modelling
by Timo Tiihonen /
2016 / English / PDF
4.7 MB Download
This book provides a thorough introduction to the challenge of
applying mathematics in real-world scenarios. Modelling tasks
rarely involve well-defined categories, and they often require
multidisciplinary input from mathematics, physics, computer
sciences, or engineering. In keeping with this spirit of
modelling, the book includes a wealth of cross-references between
the chapters and frequently points to the real-world context.
This book provides a thorough introduction to the challenge of
applying mathematics in real-world scenarios. Modelling tasks
rarely involve well-defined categories, and they often require
multidisciplinary input from mathematics, physics, computer
sciences, or engineering. In keeping with this spirit of
modelling, the book includes a wealth of cross-references between
the chapters and frequently points to the real-world context.
The book combines classical approaches to modelling with novel
areas such as soft computing methods, inverse problems, and model
uncertainty. Attention is also paid to the interaction between
models, data and the use of mathematical software. The reader
will find a broad selection of theoretical tools for practicing
industrial mathematics, including the analysis of continuum
models, probabilistic and discrete phenomena, and asymptotic and
sensitivity analysis.
The book combines classical approaches to modelling with novel
areas such as soft computing methods, inverse problems, and model
uncertainty. Attention is also paid to the interaction between
models, data and the use of mathematical software. The reader
will find a broad selection of theoretical tools for practicing
industrial mathematics, including the analysis of continuum
models, probabilistic and discrete phenomena, and asymptotic and
sensitivity analysis.
