Modeling and Simulation in Python introduces fundamental computational modeling techniques that are used in a variety of science and engineering disciplines. It emphasizes algorithmic thinking skills using different computational environments, and includes a number of interesting examples, including Shakespeare, movie databases, and virus spread.

Jason M. Kinser is Chair of the Department of Computational and Data Sciences at George Mason University. Dr. Kinser has taught more than 30 different courses at Mason in several departments including Computational & Data Sciences, Physics, Bioinformatics, Forensics, and even Biology. His research interests include analysis of images, fusion of image content non-image data, and education.

Preface

Software

1. Introduction

2. Random Values

3. Application of Random Values

4. The Monte Carlo Method

5. Modeling Self-Organization

6. Hidden Markov Models

7. Identification of Start Codons

8. HMM Application in Baseball

9. Hidden Shakespeare Model

10. Connected Data

11. Gene Expression Arrays

12. Simultaneous Equations

13. Simulations of Motion

14. Oscillations

15. Coupled Differential Equations

16. Extraordinary Number of Solutions

17. Agent Based Modeling - Virus Spread

18. Chess

Bibliography

Index