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

Next steps for simulation modeling

For most of human history, it has been reasonable to expect that when you die, the world will not be significantly different from when you were born. Over the past 300 years, this assumption has become increasingly outdated. This is because technological progress is continuously accelerating. Technological evolution translates into a next-generation product better than the previous one. This product is therefore a more efficient and effective way of developing the next stage of evolutionary progress. It is a positive feedback circuit. In other words, we are using more powerful and faster tools to design and build more powerful and faster tools. Consequently, the rate of progress of an evolutionary process increases exponentially over time, and the benefits such as speed, economy, and overall power also increase exponentially over time. As an evolutionary process becomes more effective and/or efficient, more resources are then used to encourage the...