Items related to Numerical Data Fitting in Dynamical Systems: A Practical...
Numerical Data Fitting in Dynamical Systems: A Practical Introduction with Applications and Software (Applied Optimization) - Softcover
Synopsis
Preface. 1: Introduction. 2. Mathematical Foundations. 1. Optimality Criteria. 2. Sequential Quadratic Programming Methods. 3. Least Squares Methods. 4. Numerical Solution of Ordinary Differential Equations. 5. Numerical Solution of Differential Algebraic Equations. 6. Numerical Solution of One-Dimensional Partial Differential Equations. 7. Laplace Transforms. 8. Automatic Differentiation. 9. Statistical Interpretation of Results. 3: Data Fitting Models. 1. Explicit Model Functions. 2. Laplace Transforms. 3. Steady State Equations. 4.Ordinary Differential Equations. 5. Partial Differential Equations. 6. Optimal Control Problems. 4: Numerical Experiments. 1. Test Environment. 2. Numerical Pitfalls. 3. Testing the Validity of Models. 4. Performance Evaluation. 5: Case Studies. 1. Linear Pharmacokinetics. 2. Receptor-Ligand Binder Study. 3. Robot Design. 4. Multibody System of a Truck. 5. Binary Distillation Column. 6. Acetylene Reactor. 7. Transdermal Application of Drugs. 8. Groundwater Flow. 9. Cooling a Hot Strip Mill. 10. Drying Maltodextrin in a Convection Oven. 11. Fluid Dynamics of Hydro Systems. Appendix A: Software Installation. 1. Hardware and Software Requirements. 2. System Setup. 3. Packing List. Appendix B: Test Examples. 1. Explicit Model Functions. 2. Laplace Transforms. 3. Steady State Equations. 4. Ordinary Differential Equations. 5. Differential Algebraic Equations. 6. Partial Differential Equations. 7. Partial Differential Algebraic Equations. Appendix C: The PCOMP Language. Appendix D: Generation of Fortran Code. 1. Model Equations. 2. Execution of Generated Code. References. Index.
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About the Author
Dr. Klaus Schittkowski, Full Professor
University of Bayreuth, Germany
5 books published
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