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Hands-On Simulation Modeling with Python

You're reading from Hands-On Simulation Modeling with Python Develop simulation models for improved efficiency and precision in the decision-making process

Product type Paperback

Published in Nov 2022

Publisher Packt

ISBN-13 9781804616888

Length 460 pages

Edition 2nd Edition

Languages

Python

Tools

Google cloud buildpack

Concepts

Machine Learning

Author (1):

Giuseppe Ciaburro

View More author details

Table of Contents (19) Chapters

Preface

1. Part 1:Getting Started with Numerical Simulation

2. Chapter 1: Introducing Simulation Models FREE CHAPTER

3. Chapter 2: Understanding Randomness and Random Numbers

4. Chapter 3: Probability and Data Generation Processes

5. Part 2:Simulation Modeling Algorithms and Techniques

6. Chapter 4: Exploring Monte Carlo Simulations

7. Chapter 5: Simulation-Based Markov Decision Processes

8. Chapter 6: Resampling Methods

9. Chapter 7: Using Simulation to Improve and Optimize Systems

10. Chapter 8: Introducing Evolutionary Systems

11. Part 3:Simulation Applications to Solve Real-World Problems

12. Chapter 9: Using Simulation Models for Financial Engineering

13. Chapter 10: Simulating Physical Phenomena Using Neural Networks

14. Chapter 11: Modeling and Simulation for Project Management

15. Chapter 12: Simulating Models for Fault Diagnosis in Dynamic Systems

16. Chapter 13: What’s Next?

17. Index

Why subscribe?

18. Other Books You May Enjoy

Technical requirements

In this chapter, we will provide an introduction to Monte Carlo simulation. To deal with the topics in this chapter, it is necessary to have a basic knowledge of algebra and mathematical modeling.

To work with the Python code in this chapter, you’ll need the following files (available on GitHub at the following URL: https://github.com/PacktPublishing/Hands-On-Simulation-Modeling-with-Python-Second-Edition):

simulating_pi.py
central_limit_theorem.py
numerical_integration.py
sensitivity_analysis.py
cross_entropy.py
cross_entropy_loss_function.py

The rest of the chapter is locked

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Authors (1)

Giuseppe Ciaburro

Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).

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