- 460 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Applied Parameter Estimation for Chemical Engineers
About this book
This book determines adjustable parameters in mathematical models that describe steady state or dynamic systems, presenting the most important optimization methods used for parameter estimation. It focuses on the Gauss-Newton method and its modifications for systems and processes represented by algebraic or differential equation models.
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Yes, you can access Applied Parameter Estimation for Chemical Engineers by Peter Englezos,Nicolas Kalogerakis in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Chemistry. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Dedication
- Preface
- Table of Contents
- 1: Introduction
- 2: Formulation of the Parameter Estimation Problem
- 3: Computation of Parameters in Linear Models - Linear Regression
- 4: Gauss-Newton Method for Algebraic Models
- 5: Other Nonlinear Regression Methods for Algebraic Models
- 6: Gauss-Newton Method for Ordinary Differential Equation (ODE) Models
- 7: Shortcut Estimation Methods for ODE Models
- 8: Practical Guidelines for Algorithm Implementation
- 9: Constrained Parameter Estimation
- 10: Gauss-Newton Method for Partial Differential Equation (PDE) Models
- 11: Statistical Inferences
- 12: Design of Experiments
- 13: Recursive Parameter Estimation
- 14: Parameter Estimation in Nonlinear Thermodynamic Models: Cubic Equations of State
- 15: Parameter Estimation in Nonlinear Thermodynamic Models: Activity Coefficients
- 16: Parameter Estimation in Chemical Reaction Kinetic Models
- 17: Parameter Estimation in Biochemical Engineering Models
- 18: Parameter Estimation in Petroleum Engineering
- Appendix 1
- Appendix 2
- Index