Introduction to Mathematical Modeling and Computer Simulations

Introduction to Mathematical Modeling and Computer Simulations
Author: Vladimir Mityushev
Publisher: CRC Press
Total Pages: 202
Release: 2018-02-19
Genre: Mathematics
ISBN: 1351998757

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Introduction to Mathematical Modeling and Computer Simulations is written as a textbook for readers who want to understand the main principles of Modeling and Simulations in settings that are important for the applications, without using the profound mathematical tools required by most advanced texts. It can be particularly useful for applied mathematicians and engineers who are just beginning their careers. The goal of this book is to outline Mathematical Modeling using simple mathematical descriptions, making it accessible for first- and second-year students.

Mathematical Modeling and Computer Simulation

Mathematical Modeling and Computer Simulation
Author: Daniel P. Maki
Publisher: Cengage Learning
Total Pages: 312
Release: 2006
Genre: Computers
ISBN:

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Daniel Maki and Maynard Thompson provide a conceptual framework for the process of building and using mathematical models, illustrating the uses of mathematical and computer models in a variety of situations.

Mathematical Modeling and Simulation

Mathematical Modeling and Simulation
Author: Kai Velten
Publisher: John Wiley & Sons
Total Pages: 362
Release: 2009-06-01
Genre: Science
ISBN: 3527627618

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This concise and clear introduction to the topic requires only basic knowledge of calculus and linear algebra - all other concepts and ideas are developed in the course of the book. Lucidly written so as to appeal to undergraduates and practitioners alike, it enables readers to set up simple mathematical models on their own and to interpret their results and those of others critically. To achieve this, many examples have been chosen from various fields, such as biology, ecology, economics, medicine, agricultural, chemical, electrical, mechanical and process engineering, which are subsequently discussed in detail. Based on the author`s modeling and simulation experience in science and engineering and as a consultant, the book answers such basic questions as: What is a mathematical model? What types of models do exist? Which model is appropriate for a particular problem? What are simulation, parameter estimation, and validation? The book relies exclusively upon open-source software which is available to everybody free of charge. The entire book software - including 3D CFD and structural mechanics simulation software - can be used based on a free CAELinux-Live-DVD that is available in the Internet (works on most machines and operating systems).

An Introduction to Mathematical Modeling

An Introduction to Mathematical Modeling
Author: Edward A. Bender
Publisher: Courier Corporation
Total Pages: 273
Release: 2012-05-23
Genre: Mathematics
ISBN: 0486137120

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Employing a practical, "learn by doing" approach, this first-rate text fosters the development of the skills beyond the pure mathematics needed to set up and manipulate mathematical models. The author draws on a diversity of fields — including science, engineering, and operations research — to provide over 100 reality-based examples. Students learn from the examples by applying mathematical methods to formulate, analyze, and criticize models. Extensive documentation, consisting of over 150 references, supplements the models, encouraging further research on models of particular interest. The lively and accessible text requires only minimal scientific background. Designed for senior college or beginning graduate-level students, it assumes only elementary calculus and basic probability theory for the first part, and ordinary differential equations and continuous probability for the second section. All problems require students to study and create models, encouraging their active participation rather than a mechanical approach. Beyond the classroom, this volume will prove interesting and rewarding to anyone concerned with the development of mathematical models or the application of modeling to problem solving in a wide array of applications.

Introduction to Mathematical Modeling of Crop Growth

Introduction to Mathematical Modeling of Crop Growth
Author: Christopher B. S. Teh
Publisher: Dissertation.com
Total Pages: 278
Release: 2006
Genre: Technology & Engineering
ISBN: 1581129998

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Learning mathematical modeling need not be difficult. Unlike other books, this book not only lists the equations one-by-one, but explains in detail how they are each derived, used, and finally assembled into a computer program for model simulations. This book shows how mathematics is applied in agriculture, in particular to modeling the growth and yield of a generic crop. Topics covered are agriculture meteorology, solar radiation interception and absorption, evapotranspiration, energy and soil water balance, soil water flow, photosynthesis, respiration, and crop growth development. Rather than covering many modeling approaches but in superficial detail, this book selects one or two widely-used modeling approaches and discusses about them in depth. Principles learned from this book equips readers when they encounter other modeling approaches or when they develop their own crop models.

Introduction to Modeling and Simulation with MATLAB® and Python

Introduction to Modeling and Simulation with MATLAB® and Python
Author: Steven I. Gordon
Publisher: CRC Press
Total Pages: 211
Release: 2017-07-12
Genre: Computers
ISBN: 1498773885

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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. 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. 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. 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. 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.

Mathematical Modeling and Simulation

Mathematical Modeling and Simulation
Author: Kai Velten
Publisher: John Wiley & Sons
Total Pages: 498
Release: 2024-10-07
Genre: Science
ISBN: 3527414142

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Learn to use modeling and simulation methods to attack real-world problems, from physics to engineering, from life sciences to process engineering Reviews of the first edition (2009): "Perfectly fits introductory modeling courses [...] and is an enjoyable reading in the first place. Highly recommended [...]" —Zentralblatt MATH, European Mathematical Society, 2009 "This book differs from almost all other available modeling books in that [the authors address] both mechanistic and statistical models as well as 'hybrid' models. [...] The modeling range is enormous." —SIAM Society of Industrial and Applied Mathematics, USA, 2011 This completely revised and substantially extended second edition answers the most important questions in the field of modeling: What is a mathematical model? What types of models do exist? Which model is appropriate for a particular problem? What are simulation, parameter estimation, and validation? What kind of mathematical problems appear and how can these be efficiently solved using professional free of charge open source software? The book addresses undergraduates and practitioners alike. Although only basic knowledge of calculus and linear algebra is required, the most important mathematical structures are discussed in sufficient detail, ranging from statistical models to partial differential equations and accompanied by examples from biology, ecology, economics, medicine, agricultural, chemical, electrical, mechanical, and process engineering. About 200 pages of additional material include a unique chapter on virtualization, Crash Courses on the data analysis and programming languages R and Python and on the computer algebra language Maxima, many new methods and examples scattered throughout the book and an update of all software-related procedures and a comprehensive book software providing templates for typical modeling tasks in thousands of code lines. The book software includes GmLinux, an operating system specifically designed for this book providing preconfigured and ready-to-use installations of OpenFOAM, Salome, FreeCAD/CfdOF workbench, ParaView, R, Maxima/wxMaxima, Python, Rstudio, Quarto/Markdown and other free of charge open source software used in the book.

Introduction to Mathematical Biology

Introduction to Mathematical Biology
Author: Ching Shan Chou
Publisher: Springer
Total Pages: 174
Release: 2016-04-27
Genre: Mathematics
ISBN: 3319296388

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This book is based on a one semester course that the authors have been teaching for several years, and includes two sets of case studies. The first includes chemostat models, predator-prey interaction, competition among species, the spread of infectious diseases, and oscillations arising from bifurcations. In developing these topics, readers will also be introduced to the basic theory of ordinary differential equations, and how to work with MATLAB without having any prior programming experience. The second set of case studies were adapted from recent and current research papers to the level of the students. Topics have been selected based on public health interest. This includes the risk of atherosclerosis associated with high cholesterol levels, cancer and immune interactions, cancer therapy, and tuberculosis. Readers will experience how mathematical models and their numerical simulations can provide explanations that guide biological and biomedical research. Considered to be the undergraduate companion to the more advanced book "Mathematical Modeling of Biological Processes" (A. Friedman, C.-Y. Kao, Springer – 2014), this book is geared towards undergraduate students with little background in mathematics and no biological background.

Modeling and Computer Simulation

Modeling and Computer Simulation
Author: Dragan Cvetković
Publisher: BoD – Books on Demand
Total Pages: 88
Release: 2019-04-10
Genre: Computers
ISBN: 1789857953

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Computer simulation or a computer model has the task of simulating the behaviour of an abstract model of a particular system. Computer simulations have become a useful part of mathematical modeling of many natural systems in physics, quantum mechanics, chemistry, biology, economic systems, psychology, and social sciences, as well as in the engineering process of new technologies. The authors of the five chapters have presented various applications of computer simulations as well as their advantages and disadvantages. They describe the process of modeling and its simulation of heat recovery steam generators, the chronometer detent escapement mechanism, relevant sociotechnical processes with regard to new housing and building law and regional management trends in the European Union, and the agent-based model for biological systems.

Introduction to Computational Cardiology

Introduction to Computational Cardiology
Author: Boris Ja. Kogan
Publisher: Springer Science & Business Media
Total Pages: 236
Release: 2009-12-09
Genre: Computers
ISBN: 0387766863

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Introduction to Computational Cardiology provides a comprehensive, in-depth treatment of the fundamental concepts and research challenges involved in the mathematical modeling and computer simulation of dynamical processes in the heart, under normal and pathological conditions. About this textbook: - Presents descriptions of models used in both biology and medicine for discovering the mechanisms of heart function and dysfunction on several physiological scales across different species. - Provides several examples throughout the textbook and exercises at the end which facilitate understanding of basic concepts and introduces, for implementation, treated problems to parallel supercomputers. Introduction to Computational Cardiology serves as a secondary textbook or reference book for advanced-level students in computer science, electrical engineering, biomedical engineering, and cardiac electrophysiology. It is also suitable for researchers employing mathematical modeling and computer simulations of biomedical problems.