Book Image

Hands-On Simulation Modeling with Python

By : Giuseppe Ciaburro
Book Image

Hands-On Simulation Modeling with Python

By: Giuseppe Ciaburro

Overview of this book

Simulation modeling helps you to create digital prototypes of physical models to analyze how they work and predict their performance in the real world. With this comprehensive guide, you'll understand various computational statistical simulations using Python. Starting with the fundamentals of simulation modeling, you'll understand concepts such as randomness and explore data generating processes, resampling methods, and bootstrapping techniques. You'll then cover key algorithms such as Monte Carlo simulations and Markov decision processes, which are used to develop numerical simulation models, and discover how they can be used to solve real-world problems. As you advance, you'll develop simulation models to help you get accurate results and enhance decision-making processes. Using optimization techniques, you'll learn to modify the performance of a model to improve results and make optimal use of resources. The book will guide you in creating a digital prototype using practical use cases for financial engineering, prototyping project management to improve planning, and simulating physical phenomena using neural networks. By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.
Table of Contents (16 chapters)
Section 1: Getting Started with Numerical Simulation
Section 2: Simulation Modeling Algorithms and Techniques
Section 3: Real-World Applications

Chapter 1: Introducing Simulation Models

A simulation model is a tool capable of processing information and data and predicting the responses of a real system to certain inputs, thus becoming an effective support for analysis, performance evaluation, and decision-making processes. The term simulation refers to reproducing the behavior of a system. In general, we speak of simulation both in the case in which a concrete model is used and in the case in which an abstract model is used that reproduces reality using a computer. An example of a concrete model is a scale model of an airplane that is then placed in a wind tunnel to carry out simulated tests to estimate suitable performance measures.

Although, over the years, physicists have developed theoretical laws that we can use to obtain information on the performance of dynamic systems, often, the application of these laws to a real case takes too long. In these cases, it is convenient to construct a numerical simulation model that allows us to simulate the behavior of the system under certain conditions. This elaborated model will allow us to test the functionality of the system in a simple and immediate way, saving considerable resources in terms of time and money.

In this chapter, we're going to cover the following main topics:

  • Introducing simulation models
  • Classifying simulation models
  • Approaching a simulation-based problem
  • Dynamical systems modeling

    Important Note

    In this chapter, an introduction to simulation techniques will be discussed. In order to deal with the topics at hand, it is necessary that you have a basic knowledge of algebra and mathematical modeling.