This book provides interdisciplinary and integrative overview of mathematical modeling, making it a complete textbook for a wide audience. This book is aimed at newcomers who desires to learn mathematical modeling, especially students taking a first course in the subject.
This book provides interdisciplinary and integrative overview of mathematical modeling, making it a complete textbook for a wide audience. This book is aimed at newcomers who desires to learn mathematical modeling, especially students taking a first course in the subject.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Sandip Banerjee is a Professor in the Department of Mathematics, Indian Institute of Technology Roorkee (IITR), India. His areas of research is Mathematical Biology. Mathematical modeling is his passion. Prof. Banerjee was the recipient of the Indo-US Fellowship in 2009 and he was awarded IUSSTF Research Fellow medal by the Indo-US Technology Forum. In addition to several national and international projects, Prof. Banerjee is involved in the Virtual Network in Mathematical Biology project, which promotes Mathematical Biology in India. He has also developed several courses like Differential Equations and Numerical Analysis for e-Pathshala and National Programme on Technology Enhanced Learning (NPTEL) projects, initiated by Ministry of Human Resource Development (MHDR) India.
Inhaltsangabe
1. About Mathematical Modeling. 1.1. What is Mathematical Modeling? 1.2. History of Mathematical Modeling. 1.3. Importance of Mathematical Modeling. 1.4. Latest Developments in Mathematical Modeling. 1.5. Limitations of Mathematical Modeling. 1.6. Units. 1.7. Dimensions. 1.8. Dimensional Analysis. 1.9. Scaling. 1.10. How to built Mathematical Models. 1.11. Mathematical Models and Functions. 1.12. Functional Responses in Population Dynamics. 1.13. Miscellaneous Examples. 1.14. Exercises. 2. Discrete Models using Difference Equations. 2.1. Difference Equations. 2.2. Introduction to Discrete Models. 2.3. Linear Models. 2.4. Non-Linear Models. 2.5. Bifurcations in Discrete Models. 2.6. Chaos in Discrete Models. 2.7. Miscellaneous Examples. 2.8. Mathematica Codes. 2.9. Matlab Codes. 2.10. Exercises. 2.11. Projects. 3. Continuous Models using Ordinary Differential Equations. 3.1. Introduction to Continuous Models. 3.2. Steady State Solution. 3.3. Stability. 3.4. Phase Plane Diagrams of Linear Systems. 3.5. Continuous Models. 3.6. Bifurcations. 3.7. Estimation of Model Parameters. 3.8. Chaos in Continuous Models. 3.9. Miscellaneous Examples. 3.10. Mathematica Codes. 3.11. Matlab Codes. 3.12. Exercises. 3.13. Projects. 4. Spatial Models using Partial Differential Equations. 4.1. Introduction. 4.2. Heat Flow through a Small Thin Rod (One Dimensional). 4.3. Two dimensional Heat-equation (Diffusion equation). 4.4. Steady Heat Flow: Laplace equation. 4.5. Wave Equation. 4.6. Two dimensional Wave Equation. 4.7. Fluid Flow through a Porous Medium. 4.8. Traffic Flow. 4.9. Crime Model. 4.10. Reaction Diffusion Systems. 4.11. Mathematica Codes. 4.12. Matlab Codes. 4.13. Miscellaneous Examples. 4.14. Exercises. 4.15. Project. 5. Modeling with Delay Differential Equations. 5.1. Introduction. 5.2. Linear Stability Analysis. 5.3. Different Models with Delay Differential Equations. 5.4. Immunotherapy with Interleukin-2, a study based on Mathematical Modeling. 5.5. Miscellaneous Examples. 5.6. Mathematica Codes. 5.7. Matlab Codes. 5.8. Exercises. 5.9. Project. 6. Modeling with Stochastic Differential Equations. 6.1. Introduction. 6.2. Stochastic Models. 6.3. Research Problem: Cancer Self-Remission and Tumor Stability - a stochastic approach. 6.4. Mathematica Codes. 6.5. Matlab Codes. 6.6. Exercises. 7. Hints and Solutions. Bibliography. Index.
