Mathematical Modelling

ISBN-13: 9783319802268 / Angielski / Miękka / 2018 / 242 str.

Seppo Pohjolainen; Matti Heilio; Timo Lahivaara

Recenzje

"Mathematical modelling is a product of several different contributors, all from Finnish universities. The result is a text used by over 2,000 students. ... This is an excellent book, written with a myriad of interesting and very practical problems and applications. The contributors to the text are obviously scientific scholars who are elegantly educated." (James Van Speybroeck, Computing Reviews, March, 2017)  

O autorze

Seppo Pohjolainen received his PhD degree in applied mathematics in 1980 from Tampere University of Technology (TUT). In 1998 he was appointed as a professor in mathematics at TUT.   

His research interests include mathematical control theory, distributed parameter systems, mathematical modelling and simulation, development and use of information technology to support learning. Currently he is leading a nationwide network in Finland on teaching mathematical modelling on the Internet. He has led several national and international research projects and written a number of journal articles and conference papers on all these fields. 

 

                          

Blurb

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.