Simulation with Python Develop Simulation and Modeling in Natural Sciences, Engineering, and Social Sciences

Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms us...

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Bibliographic Details
Main Authors: Li, Rongpeng, Nakano, Aiichiro (Author)
Format: eBook
Language:English
Published: Berkeley, CA Apress 2022, 2022
Edition:1st ed. 2022
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Simulation with Python  |h Elektronische Ressource  |b Develop Simulation and Modeling in Natural Sciences, Engineering, and Social Sciences  |c by Rongpeng Li, Aiichiro Nakano 
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260 |a Berkeley, CA  |b Apress  |c 2022, 2022 
300 |a XV, 166 p. 90 illus., 80 illus. in color  |b online resource 
505 0 |a Chapter 1: Calculating Pi and Beyond: Searching Order in Disorder with Simulation -- Chapter 2: Markov Chain: A Peek into the Future.Chapter 3: Multi-Armed Bandits: Probability Simulation and Bayesian Statistics -- Chapter 4: Balls in 2D Box: A Simplest Physics Engine -- Chapter 5: Percolation: Threshold and Phase Change -- Chapter 6: Queuing System: How Stock Trades are Made -- Chapter 7: Rock, Scissor and Paper: Multi-Agent Simulation -- Chapter 8: Matthew Effect and Tax Policy: Why the Rich Keeps Getting Richer -- Chapter 9: Misinformation Spreading: Simulation on a Graph (Centrality, Networkx) -- Chapter 10: Simulated Annealing and Genetic Algorithm 
653 |a Artificial intelligence / Data processing 
653 |a Programming languages (Electronic computers) 
653 |a Python 
653 |a Programming Language 
653 |a Python (Computer program language) 
653 |a Data Science 
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520 |a Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated. After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python. You will: Use Python and numerical computation to demonstrate the power of simulation Choose a paradigm to run a simulation Draw statistical insights from numerical experiments Know how simulation is used to solve real-world problems