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Total Size:
17.9 MB
Info Hash:
846C68BA7CF3A7288CCBBFA66E1F6BB59FB88B10
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Added:
April 23, 2026, 3:46 a.m.
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(Last updated: April 23, 2026, 3:47 a.m.)
| File | Size |
|---|---|
| Mityushev V. Introduction to Mathematical Modeling and Computer Simulations 2024.pdf | 17.9 MB |
NOTE
SOURCE: Mityushev V. Introduction to Mathematical Modeling and Computer Simulations 2024
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COVER
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MEDIAINFO
Textbook in PDF format Introduction to Mathematical Modeling and Computer Simulations, Second Edition continues to serve as an engaging and accessible textbook for undergraduates studying mathematical modeling and computer simulations. The book is heavily focussed on applications, and so may have a particular appeal to applied mathematicians, engineers, and others working in applied quantitative disciplines. The book may also be useful as a reference text for reference text for early-career stage practitioners. Much has happened in mathematical modeling and computer simulation since the ?rst edition of this book. A modern course in this field has to include Machine Learning and Artificial Intelligence (AI). To take into account this requirement we made this mathematical book less mathematical trying to find the common point: less pure mathematical theory and more constructive algorithms and rules. The new Chapter 10, Machine Learning and data analysis, has been added. Moreover, an elementary introduction to programming in the Python language can be found in Appendix A. We use the standard Python code coloring scheme in Chapter 10 which differs from the style of other chapters. The Jupyter notebooks with examples for Chapter 10 and Appendix A can be downloaded from the Publisher’s. We checked that they can run on Google Colab without any problems. If you try to run it on your local Jupyter Notebooks installation, it is possible that you will have to install additional free Python packages – the procedure of installation is described in Appendix A.2.8. We provide some example Python codes, however, it is a good exercise to rewrite the Mathematica and MatLAB codes into Python code to gain ?uency. Chapter 9, ‘Asymptotic Methods in Composites’, has been entirely re-written to make it more consistent with industry and scientific standards
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