Mathematical Modeling and Computer Simulation
Published on 6. January 2005
Book
Hardback
450 pages
978-0-534-38478-4 (ISBN)
Description
Learn to build and use mathematical models with MATHEMATICAL MODELING AND COMPUTER SIMULATION! Through the description of mathematical and computer models in a variety of situations, this mathematics text helps you learn that model building is a dynamic process involving simplification, approximation, abstraction, analysis, computation, and comparison. Case studies illustrate how the model building process is applied to real life situations arising in a variety of settings, including business, genetics, population biology, and social science. An appendix on student projects provides you with a selection of classroom-tested projects with hints and suggestions for organizing project work and communicating results.
More details
Language
English
Place of publication
CA
United States
Publishing group
Cengage Learning, Inc
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 236 mm
Width: 168 mm
Thickness: 23 mm
Weight
560 gr
ISBN-13
978-0-534-38478-4 (9780534384784)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Content
1. BASIC PRINCIPLES. Overview of the Uses of the Term Model. The Process of Constructing Mathematical Models. Types of Mathematical Models. A Classic Example. Axiom Systems and Models. Simulation Models. Practical Aspects of Model Building. 2. MODEL BUILDING: SELECTED CASE STUDIES. Introduction. Mendelian Genetics. Models for Growth Processes. Social Choice. Moving Mobile Homes. A Stratified Population Model. Selected Simulations. Waiting in Line Again! Estimating Parameters and Testing Hypotheses. 3. MARKOV CHAINS. Introduction. The Setting and Some Examples. Basic Properties of Markov Chains. Regular Markov Chains. Absorbing Chains and Applications. 4. SIMULATION MODELS. Introduction. The Simulation Process. Discrete Random Variables. Discrete Event Simulation. Continuous Random Variables. Applications. 5. LINEAR PROGRAMMING MODELS. Introduction. Formulation of Linear Programming Problems. Linear Programming Problems and Duality. Duality, Sensitivity, and Uncertainty. Job Assignment. Networks and Flows. Appendix A: Projects and Presentations. Introduction. Types of Projects. Examples of Projects. Reports and Presentations. Evaluating Project Reports. Sources of Projects.