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Simulation with Python = develop sim...

Li, Rongpeng.

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Simulation with Python = develop simulation and modeling in natural sciences, engineering, and social sciences /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Simulation with Python/ by Rongpeng Li, Aiichiro Nakano.
Reminder of title:	develop simulation and modeling in natural sciences, engineering, and social sciences /
Author:	Li, Rongpeng.
other author:	Nakano, Aiichiro.
Published:	Berkeley, CA :Apress : : 2022.,
Description:	xv, 166 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Python (Computer program language) -
Online resource:	https://doi.org/10.1007/978-1-4842-8185-7
ISBN:	9781484281857

Simulation with Python = develop simulation and modeling in natural sciences, engineering, and social sciences /
Li, Rongpeng.

Simulation with Pythondevelop simulation and modeling in natural sciences, engineering, and social sciences /[electronic resource] :by Rongpeng Li, Aiichiro Nakano. - Berkeley, CA :Apress :2022. - xv, 166 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9781484281857

Standard No.: 10.1007/978-1-4842-8185-7doiSubjects--Topical Terms:

729789
Python (Computer program language)

LC Class. No.: QA76.73.P98 / L52 2022

Dewey Class. No.: 003.3

Simulation with Python = develop simulation and modeling in natural sciences, engineering, and social sciences /
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245 1 0 $a Simulation with Python $h [electronic resource] : $b develop simulation and modeling in natural sciences, engineering, and social sciences / $c by Rongpeng Li, Aiichiro Nakano.
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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.
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.
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