Applied Mathematics with Open-Source Software: Operational Research Problems with Python and R

Book Description

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.

Features

• 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.

中文：

书名：应用数学与开源软件：使用Python和R的运筹学问题

应用数学与开源软件：使用Python和R的运筹学问题
面向广大读者，他们希望学习如何使用开源软件来解决应用数学中的问题。这本书有一个创新的结构，由两个章节组成的4节，涵盖了广泛的应用数学技术：概率建模、动力系统、紧急行为和优化。每一节中的章节对演示了不同的解决方法系列。每一章都从一个问题开始，给出了相关理论的概述，展示了在R和Python语言中的解决方法，最后通过包括一些已发表的参考文献给出了更广泛的背景。这种结构将允许最大程度的可访问性，只需最少的数学或编程先决条件，并为想要深入研究特定主题的读者提供合适的机会。

功能

• 对于应用数学和运筹学的学者，以及任何想要学习如何使用开源软件的学者来说，这是一个极好的资源。
• 与其他文本相比，无论是在编程语言方面，还是在所考虑的主题方面，都提供了更一般和更容易理解的主题。
• R节和Python节故意相互镜像，以便读者只能阅读他们感兴趣的节。
• 附带的开源资源库包含源文件和更多示例，网址为：https：//bit.ly/3kpoKSd。