Fitting Curves And Sourfaces Using Matlab
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Curve and Surface Fitting with Splines
Describes the algorithms and mathematical fundamentals of a widely-used FORTRAN package for curve and surface fitting with splines.
CURVE and SURFACE FITTING with MATLAB. LINEAR and NONLINEAR REGRESSION
You can fit curves and surfaces to data and view plots with the Curve Fitting app in MATLAB. Is possible: .Create, plot, and compare multiple fits.Use linear or nonlinear regression, interpolation, smoothing, and custom equations..View goodness-of-fit statistics, display confidence intervals and residuals, remove outliers and assess fit with validation data..Automatically generate code to fit and plot curves and surfaces, or export fits to the workspace for further analysis.Curve Fitting app makes it easy to plot and analyze fit at the command line. You can export individual fit to the workspace for further analysis, or you can generate MATLAB code to recreate all fit and plots in your session. By generating code, you can use your interactive curve fitting session to quickly assemble code for curve and surface fit and plots into useful programs.The Curve Fitting app allows convenient, interactive use of Curve Fitting Toolbox functions, without programming. You can, however, access Curve Fitting Toolbox functions directly, and write programs that combine curve fitting functions with MATLAB functions and functions from other toolboxes. This allows you to create a curve fitting environment that is precisely suited to your needs. Models and fit in the Curve Fitting app are managed internally as curve fitting objects. Objects are manipulated through a variety of functions called methods. You can create curve fitting objects, and apply curve fitting methods, outside of the Curve Fitting app
Chemical Engineering Analysis and Optimization Using MATLAB
Tackle challenging optimization problems with MATLAB software Optimization techniques are used to measure the minimum or maximum value of a given function depending on circumstances and key factors. Engineering processes pertaining to design or manufacture involve optimization techniques at every stage, designed to minimize resource expenditure and maximize outcomes. Optimization problems are difficult and computationally intensive, but the increasingly widely-used MATLAB platform offers numerous tools by which engineers can tackle these essential elements of process and industrial design. Chemical Engineering Analysis and Optimization Using MATLAB offers an introduction to the cutting-edge, highly in-demand skills of computer-aided design and optimization. With a focus on chemical engineering analysis, the book uses the MATLAB platform to develop reader skills in programming, modeling, and more. It provides an overview of some of the most essential tools in modern engineering design. Chemical Engineering Analysis and Optimization Using MATLAB readers will also find: Case studies for developing specific skills in MATLAB and beyond Examples of code both within the text and on companion website End of chapter problems with accompanying solutions manual for instructors This textbook is ideal for advanced undergraduate and graduate students in chemical engineering and related disciplines, as well as professionals with backgrounds in engineering design.