Scientific Computing, Simulations, and Modeling
- Page ID
- 53717
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These texts are intended for students interested in developing a deeper understanding and appreciation of how natural and human-generated systems such as weather, biological processes, supply chains, or computers that can be represented by mathematical models and computer software. These models are often described and represented by mathematical expressions and the models themselves often deal with physical phenomena.
- Book: Introduction to Social Network Methods (Hanneman)
- This on-line textbook introduces many of the basics of formal approaches to the analysis of social networks.
- 1: Social Network Data
- 2: Why Formal Methods?
- 3: Using Graphs to Represent Social Relations
- 4: Working with Netdraw to Visualize Graphs
- 5: Using Matrices to Represent Social Relations
- 6: Working with Network Data
- 7: Connection
- 8: Embedding
- 9: Ego Networks
- 10: Centrality and Power
- 11: Cliques and Sub-groups
- 12: Positions and Roles - The Idea of Equivalence
- 13: Measures of Similarity and Structural Equivalence
- 14: Automorphic Equivalence
- 15: Regular Equivalence
- 16: Multiplex Networks
- 17: Two-Mode Networks
- 18: Some Statistical Tools
- Front Matter
- Back Matter
- Book: Introduction to the Modeling and Analysis of Complex Systems (Sayama)
- Introduction to the Modeling and Analysis of Complex Systems introduces students to mathematical/computational modeling and analysis developed in the emerging interdisciplinary field of Complex Systems Science. Complex systems are systems made of a large number of microscopic components interacting with each other in nontrivial ways.
- Front Matter
- 1: Introduction to Modeling and Analysis
- 2: Fundamentals of Modeling
- 3: Basics of Dynamical Systems
- 4: Discrete-Time Models I - Modeling
- 5: Discrete-Time Models II - Analysis
- 6: Continuous-Time Models I - Modeling
- 7: Continuous-Time Models II - Analysis
- 8: Bifurcations
- 9: Chaos
- 10: Interactive Simulations of Complex Systems
- 11: Cellular Automata I - Modeling
- 12: Cellular Automata II - Analysis
- 13: Continuous Field Models I - Modeling
- 14: Continuous Field Models II - Analysis
- 15: Basics of Networks
- 16: Dynamical Networks I - Modeling
- 17: Dynamical Networks II - Analysis of Network Topologies
- 18: Dynamical Networks III - Analysis of Network Dynamics
- 19: Agent-Based Models
- Back Matter
- Physical Modeling in MATLAB (Downey)
- Modeling and simulation are powerful tools for explaining the world, making predictions, designing things that work, and making them work better. Learning to use these tools can be difficult; this book is my attempt to make the experience as enjoyable and productive as possible. By reading this book—and working on the exercises—you will learn some programming, some modeling, and some simulation. With basic programming skills, you can create models for a wide range of physical systems.
- Scientific Computing (Chasnov)
- These notes for Scientific Computing is primarily for Math majors and supposes no previous knowledge of numerical analysis or methods. This course consists of both numerical methods and computational physics. The numerical methods content includes standard topics such as IEEE arithmetic, root finding, linear algebra, interpolation and least-squares, integration, differentiation, and differential equations.
- Scientific Computing (Staab)
- Solving problems is the essence of scientific computing. Many problems arise naturally from the sciences or mathematics and often to solve difficult problem relies on some computing resources. In a nutshell, this text is the blend of science, mathematics and computer science needed to solve problems. The intended audience for this text one who is interested in writing computer code that will solve a problem that you have.
- Front Matter
- 1: Introduction to Scientific Computing
- 2: Storing number and strings and using Julia syntax
- 3: Introduction to Data Types
- 4: Introduction to Functions
- 5: Boolean Statements, Loops and Branching
- 6: Arrays
- 7: Functional Programming and an Introduction to Writing fast code
- 8: Number theory and Algorithm Development
- 9: Algorithm Analysis
- 10: Solving Quadratics and Rootfinding
- 11: Plotting Data and Functions
- Back Matter
Thumbnail: A three-dimensional surface plot of the unnormalized sinc function. (Public Domain; via Wikipedia)