Описание: A solutions manual to accompany An Introduction to Discrete Mathematical Modeling with Microsoft(R) Office Excel(R)
With a focus on mathematical models based on real and current data, Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft(R) Office Excel(R)guides readers in the solution of relevant, practical problems by introducing both mathematical and Excel techniques.
The book begins with a step-by-step introduction to discrete dynamical systems, which are mathematical models that describe how a quantity changes from one point in time to the next. Readers are taken through the process, language, and notation required for the construction of such models as well as their implementation in Excel. The book examines single-compartment models in contexts such as population growth, personal finance, and body weight and provides an introduction to more advanced, multi-compartment models via applications in many areas, including military combat, infectious disease epidemics, and ranking methods. Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft(R) Office Excel(R) also features:
A modular organization that, after the first chapter, allows readers to explore chapters in any order
Numerous practical examples and exercises that enable readers to personalize the presented models by using their own data
Carefully selected real-world applications that motivate the mathematical material such as predicting blood alcohol concentration, ranking sports teams, and tracking credit card debt
References throughout the book to disciplinary research on which the presented models and model parameters are based in order to provide authenticity and resources for further study
Relevant Excel concepts with step-by-step guidance, including screenshots to help readers better understand the presented material
Both mathematical and graphical techniques for understanding concepts such as equilibrium values, fixed points, disease endemicity, maximum sustainable yield, and a drug's therapeutic window
A companion website that includes the referenced Excel spreadsheets, select solutions to homework problems, and an instructor's manual with solutions to all homework problems, project ideas, and a test bank
Описание: Lattice Boltzmann models have a remarkable ability to simulate single- and multi-phase fluids and transport processes within them. A rich variety of behaviors, including higher Reynolds numbers flows, phase separation, evaporation, condensation, cavitation, buoyancy, and interactions with surfaces can readily be simulated. This book provides a basic introduction that emphasizes intuition and simplistic conceptualization of processes. It avoids the more difficult mathematics that underlies LB models. The model is viewed from a particle perspective where collisions, streaming, and particle-particle/particle-surface interactions constitute the entire conceptual framework. Beginners and those with more interest in model application than detailed mathematical foundations will find this a powerful "quick start" guide. Example simulations, exercises, and computer codes are included. Working code is provided on the Internet.
Автор: Mark Pinsky Название: An Introduction to Stochastic Modeling, ISBN: 0123814162 ISBN-13(EAN): 9780123814166 Издательство: Elsevier Science Рейтинг: Цена: 13304.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduces students to the standard concepts and methods of stochastic modeling, to illustrate the diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems.
Автор: Kinder Jesse M., Nelson Philip Название: A Student`s Guide to Python for Physical Modeling ISBN: 0691170509 ISBN-13(EAN): 9780691170503 Издательство: Wiley Рейтинг: Цена: 3168.00 р. Наличие на складе: Поставка под заказ.
Описание:
Python is a computer programming language that is rapidly gaining popularity throughout the sciences. "A Student s Guide to Python for Physical Modeling" aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed.
This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including: Basic Python programming and scriptingNumerical arraysTwo- and three-dimensional graphicsMonte Carlo simulationsNumerical methods, including solving ordinary differential equationsImage processingAnimation
Numerous code samples and exercises with solutions illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more."
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