| 000 | a | ||
|---|---|---|---|
| 999 |
_c31914 _d31914 |
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| 008 | 230420b xxu||||| |||| 00| 0 eng d | ||
| 020 | _a9780367339982 | ||
| 082 |
_a658.40340285 _bKNI |
||
| 100 | _aKnight, Vincent | ||
| 245 | _aApplied mathematics with open-source software : operational research problems with Python and R | ||
| 260 |
_bCRC Press, _a2022 _cBoca Raton : |
||
| 300 |
_aix, 142 p. ; _bill., _c26 cm |
||
| 365 |
_b44.99 _cGBP _d104.20 |
||
| 490 | _aChapman & Hall/CRC series in operations research | ||
| 504 | _aIncludes bibliographical references and index. | ||
| 520 | _aApplied Mathematics with Open-source Software: Operational Research Problems with Python and R is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics. The book has an innovative structure with 4 sections of two chapters covering a large range of applied mathematical techniques: probabilistic modelling, dynamical systems, emergent behaviour and optimisation. The pairs of chapters in each section demonstrate different families of solution approaches. Each chapter starts with a problem, gives an overview of the relevant theory, shows a solution approach in R and in Python, and finally gives wider context by including a number of published references. This structure will allow for maximum accessibility, with minimal prerequisites in mathematics or programming as well as giving the right opportunities for a reader wanting to delve deeper into a particular topic. An excellent resource for scholars of applied mathematics and operational research, and indeed any academics who want to learn how to use open-source software. Offers more general and accessible treatment of the subject than other texts, both in terms of programming language but also in terms of the subjects considered. The R and Python sections purposefully mirror each other so that a reader can read only the section that interests them. | ||
| 650 | _aMathematics Data processing | ||
| 650 | _aAxelrod | ||
| 650 | _aBoids | ||
| 650 | _aCBC MILP Solver | ||
| 650 | _aDifferential equation | ||
| 650 | _aDynamical systems | ||
| 650 | _aEmergent behaviour | ||
| 650 | _a Enler method | ||
| 650 | _aFire station location problem | ||
| 650 | _aGreen vehicle routing problem | ||
| 650 | _aLinear programming | ||
| 650 | _aMarkov chain | ||
| 650 | _a Matrix equation | ||
| 650 | _a Nash equilibrium | ||
| 650 | _aOperational research | ||
| 650 | _aProbability | ||
| 650 | _aRandom seed | ||
| 650 | _a Simplex method | ||
| 650 | _aTravelling salesman problem | ||
| 650 | _aHeuristics | ||
| 700 | _aPalmer, Geraint | ||
| 942 |
_2ddc _cBK |
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