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Applied mathematics with open-source software : operational research problems with Python and R / 1st ed

Applied mathematics with open-source software : operational research problems with Python and R / 1st ed

Material type
단행본
Personal Author
Knight, Vincent (Vincent A.). Palmer, Geraint, author.
Title Statement
Applied mathematics with open-source software : operational research problems with Python and R / Vincent Knight, Geraint Palmer.
판사항
1st ed.
Publication, Distribution, etc
Boca Raton :   C&H/CRC Press,   2022.  
Physical Medium
ix, 142 p. : ill. ; 26 cm.
Series Statement
Chapman & Hall/CRC series in operations research
ISBN
9780367348687 9780367339982
요약
"Applied 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. An accompanying open-source repository with source files and further examples is posted online at https://bit.ly/3kpoKSd"--Provided by publisher.
Bibliography, Etc. Note
Includes bibliographical references and index.
Subject Added Entry-Topical Term
Operations research --Data processing. Mathematics --Data processing. Python (Computer program language). R (Computer program language).
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100 1 ▼a Knight, Vincent ▼q (Vincent A.).
245 1 0 ▼a Applied mathematics with open-source software : ▼b operational research problems with Python and R / ▼c Vincent Knight, Geraint Palmer.
250 ▼a 1st ed.
260 ▼a Boca Raton : ▼b C&H/CRC Press, ▼c 2022.
264 1 ▼a Boca Raton : ▼b C&H/CRC Press, ▼c 2022.
300 ▼a ix, 142 p. : ▼b ill. ; ▼c 26 cm.
336 ▼a text ▼b txt ▼2 rdacontent
337 ▼a unmediated ▼b n ▼2 rdamedia
338 ▼a volume ▼b nc ▼2 rdacarrier
490 1 ▼a Chapman & Hall/CRC series in operations research
504 ▼a Includes bibliographical references and index.
520 ▼a "Applied 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. An accompanying open-source repository with source files and further examples is posted online at https://bit.ly/3kpoKSd"--Provided by publisher.
650 0 ▼a Operations research ▼x Data processing.
650 0 ▼a Mathematics ▼x Data processing.
650 0 ▼a Python (Computer program language).
650 0 ▼a R (Computer program language).
700 1 ▼a Palmer, Geraint, ▼e author.
830 0 ▼a Chapman and Hall/CRC series in operations research.
945 ▼a ITMT

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/Western Books/ Call Number 658.40340285 K71a Accession No. 111881349 Availability Available Due Date Make a Reservation Service B M

Contents information

Table of Contents

Section I. Getting Started. 1. Introduction. 1.1. Who is This Book For? 1.2. What do We Mean by Applied Mathematics? 1.3. What is Open-Source Software. 1.4. How to Get the Most Out of this Book. 1.5. How Code is Written in this Book. Section II. Probabilistic Modelling. 2. Markov Chains. 2.1. Problem. 2.2. Theory. 2.3. Solving with Python. 2.4. Solving with R. 2.5. Wider Context. 3.Discrete Event Simulation. 3.1. Problem. 3.2. Theory. 3.3. Solving with Python. 3.4. Solving with R. 3.5. Wider Context. Section III. Dynamical Systems. 4. Differential Equations. 4.1. Problem. 4.2. Theory. 4.3. Solving with Python. 4.4. Solving with R. 4.5. Wider Context. Chapter 5. Systems Dynamics. 5.1. Problem. 5.2. Theory. 5.3. Solving with Python. 5.4. Solving with R. 5.5. Wider Context. Section IV. Emergent Behaviour. 6. Game Theory. 6.1. Problem. 6.2. Theory. 6.3. Solving with Python. 6.4. Solving with R. 6.5. Wider Context. 7. Agent Based Simulation. 7.1. Problem. 7.2. Theory. 7.3. Solving with Python. 7.4. Solving with R. 7.5. Wider Context. Section V. Optimisation. 8. Linear Programming. 8.1. Problem. 8.2. Theory. 8.3. Solving with Python. 8.4. Solving with R. 8.5. Wider Context. 9. Heuristics. 9.1. Problem. 9.2. Theory. 9.3. Solving with Python. 9.4. Solving with R. 9.5. Wider Context.

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