Description
Taylor & Francis Introduction To Modeling And Simulation With Matlab® And Python by Steven I. Gordon
Introduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer modeling, as well as basic programming skills. The book content focuses on meeting a set of basic modeling and simulation competencies that were developed as part of several National Science Foundation grants. Even though computer science students are much more expert programmers, they are not often given the opportunity to see how those skills are being applied to solve complex science and engineering problems and may also not be aware of the libraries used by scientists to create those models._x000D__x000D__x000D_The book interleaves chapters on modeling concepts and related exercises with programming concepts and exercises. The authors start with an introduction to modeling and its importance to current practices in the sciences and engineering. They introduce each of the programming environments and the syntax used to represent variables and compute mathematical equations and functions. As students gain more programming expertise, the authors return to modeling concepts, providing starting code for a variety of exercises where students add additional code to solve the problem and provide an analysis of the outcomes. In this way, the book builds both modeling and programming expertise with a "just-in-time" approach so that by the end of the book, students can take on relatively simple modeling example on their own._x000D__x000D__x000D_Each chapter is supplemented with references to additional reading, tutorials, and exercises that guide students to additional help and allows them to practice both their programming and analytical modeling skills. In addition, each of the programming related chapters is divided into two parts - one for MATLAB and one for Python. In these chapters, the authors also refer to additional online tutorials that students can use if they are having difficulty with any of the topics._x000D__x000D__x000D_The book culminates with a set of final project exercise suggestions that incorporate both the modeling and programming skills provided in the rest of the volume. Those projects could be undertaken by individuals or small groups of students._x000D__x000D__x000D_The companion website at http://www.intromodeling.com provides updates to instructions when there are substantial changes in software versions, as well as electronic copies of exercises and the related code. The website also offers a space where people can suggest additional projects they are willing to share as well as comments on the existing projects and exercises throughout the book. Solutions and lecture notes will also be available for qualifying instructors._x000D_ _x000D_
INTRODUCTION TO COMPUTATIONAL MODELING_x000D_
The Importance of Computational Science_x000D_
How Modeling Has Contributed to Advances in Science and Engineering_x000D_
The Modeling Process_x000D_
Exercises_x000D_
References_x000D_
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INTRODUCTION TO PROGRAMMING ENVIRONMENTS_x000D_
The MATLAB Programming Environment_x000D_
The Python Environment_x000D_
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DETERMINISTIC LINEAR MODELS_x000D_
Selecting a Mathematical Representation for a Model _x000D_
Linear Models and Linear Equations_x000D_
Linear Interpolation_x000D_
Systems of Linear Equations_x000D_
Limitations of Linear Models_x000D_
Exercises_x000D_
References_x000D_
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ARRAY MATHEMATICS IN MATLAB AND PYTHON_x000D_
Introduction to Arrays and Matrices_x000D_
Brief Overview of Matrix Mathematics_x000D_
Matrix Operations in MATLAB_x000D_
Matrix Operations in Python_x000D_
Exercises_x000D_
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PLOTTING_x000D_
Plotting in MATLAB_x000D_
Plotting in Python_x000D_
Exercises_x000D_
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PROBLEM SOLVING_x000D_
Overview_x000D_
Bottle Filling Example_x000D_
Tools for Program Development_x000D_
Bottle Filling Example continued_x000D_
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CONDITIONAL STATEMENTS_x000D_
Relational Operators_x000D_
Logical Operators_x000D_
Conditional Statements_x000D_
Exercises_x000D_
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ITERATION AND LOOPS_x000D_
For Loops_x000D_
While Loops_x000D_
Control Statements_x000D_
Exercises_x000D_
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NON-LINEAR AND DYNAMIC MODELS_x000D_
Modeling Complex Systems_x000D_
Systems Dynamics_x000D_
Modeling Physical and Social Phenomena_x000D_
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ESTIMATING MODELS FROM EMPIRICAL DATA_x000D_
Using Data to Build Forecasting Models_x000D_
Fitting a Mathematical Function to Data_x000D_
Exercises_x000D_
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STOCHASTIC MODELS_x000D_
Introduction_x000D_
Creating a Stochastic Model_x000D_
Random Number Generators in MATLAB and Python_x000D_
A Simple Code Example_x000D_
Examples of Larger Scale Stochastic Models_x000D_
Exercises_x000D_
References _x000D_
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FUNCTIONS_x000D_
MATLAB Functions_x000D_
Python Functions_x000D_
Exercises_x000D_
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VERIFICATION, VALIDATION, AND ERRORS_x000D_
Introduction_x000D_
Errors_x000D_
Verification and Validation_x000D_
Exercises_x000D_
References _x000D_
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CAPSTONE PROJECTS_x000D_
Introduction_x000D_
Project Goals_x000D_
Project Descriptions_x000D_