Interpolation and Regression Models for the Chemical Engineer: Solving Numerical Problems

Engineers and other applied scientists are frequently faced with models of complex systems for which no rigorous mathematical solution can be calculated. Numerical approximations are thus frequently used to predict the behavior of such systems, either based on real–life measurements or on the behavior of simpler models.
An engineer′s companion for using numerical methods for the solution of complex mathematical problems. It explains the theory behind current numerical methods and shows how to use them in a step–by–step fashion, focusing on interpolation and regression models.
The methods and examples are taken from a wide range of scientific and engineering fields, including chemical and electrical engineering, physics, medicine, and environmental science.
The material is based on several courses for scientists and engineers taught by the authors, and all the exercises and problems are classroom–tested. The software needed is available by way of a freely accessible program library at the University of Milan that provides up–to–date software tools for all the methods described in the book.

Spis treści:
INTRODUCTION
Notation –
BzzMath Library Style
Basic Requirements for Using the BzzMath Library
Topics of Volume II –
Topics of Companion Volumes
INTERPOLATION
Polynomial Interpolation
Hermit Polynomial Interpolation
Interpolation with Rational Functions
Comparision between Polynomial Interpolation and Interpolation with Rational Functions
Inverse Interpolation
Successive Polynomials Interpolation
Orthogonla Polynomials
Questions –
Excercises –
References
FUNDAMENTALS OF STATISTICS
Fundamentals
Estimate of the Expected Value
Estimation of Variance
Outliers Detection
Relevant Probability Distributions
Correct Meaning of Statistical Tests and Confidence Regions
Questions –
Excercises –
References
LINEAR REGRESSIONS
Linear Models and Method of Least Squares
Hypotheses for Linear Regression Problems
Outliers Detection and Robust Regression
Homoscedasticity
Multicollinearity
BzzLinearRegression Toolkit
Questions –
Excercises –
References
NONLINEAR REGRESSIONS
Nonlinear Regression Problems
Models Reformulation
Parameters Evaluation
Outliers Detection
Parameters Estimation Improvements
Model Discrimination
Simultaneous Discrimination and Accurate Parameters Estimation
Questions –
Excercises –
References
APPENDICES

Nota biograficzna:
Guido Buzzi–Ferraris is full professor of process systems engineering at Politecnico die Milano, Italy, where he holds two courses: "Methods and Numerical Applications in Chemical Engineering" and "Regression Models and Statistics". He works on numerical analysis, statistics, differential systems, and optimization. He has authored books of international relevance on numerical analysis, such as "Scientific C++" edited by Addison–Wesley, and over than 200 papers on international magazines. He is the inventor and the developer of BzzMath library, which is currently adopted by academies, R&D groups, and industries. He is permanent member of the "EFCE Working Party – Computer Aided Process Engineering" since 1969 and editorial advisory board of "Computers & Chemical Engineering" since 1987.
Flavio Manenti is assistant professor of process systems engineering at Politecnico di Milano, Italy. He obtained his academic degree and PhD at Politecnico di Milano, where he currently collaborates with Professor Buzzi–Ferraris. He holds courses on "Process Dynamics and Control of Industrial Processes" and "Supply Chain Optimization" and he works on numerical analysis, process control and optimization. He has also received international scientific awards, such as Memorial Burianec (Prague, CZ) and E xcellence in Simulation (Lake Forest, CA, USA), for his research activities and scientific publications.


Okładka tylna:
Engineers and other applied scientists are frequently faced with models of complex systems for which no rigorous mathematical solution can be calculated. Numerical approximations are thus frequently used to predict the behavior of such systems, either based on real–life measurements or on the behavior of simpler models.
An engineer′s companion for using numerical methods for the solution of complex mathematical problems. It explains the theory behind current numerical methods and shows how to use them in a step–by–step fashion, focusing on interpolation and regression models.
The methods and examples are taken from a wide range of scientific and engineering fields, including chemical and electrical engineering, physics, medicine, and environmental science.
The material is based on several courses for scientists and engineers taught by the authors, and all the exercises and problems are classroom–tested. The software needed is available by way of a freely accessible program library at the University of Milan that provides up–to–date software tools for all the methods described in the book.