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Nonlinear Regression Modeling for Engineering Applications: Modeling, Model Validation, and Enabling Design of Experiments

By
R. Russell Rhinehart
R. Russell Rhinehart
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ISBN:
9781118597965
No. of Pages:
400
Publisher:
ASME-Wiley
Publication date:
2016

Typically, on a generic regression application such as y = a + bx + cx2 there are no constraints on the optimization. The coefficients a, b, and c could have either positive or negative values. However, in phenomenological models coefficients represent phenomena and their values are constrained. For example, a delay and a time constant must both have non-negative values. Further, in regression of a model to fit an engineering application there are many other variables to consider. One application could be to fit a distillation column tray-to-tray model to data by adjusting coefficients representing tray efficiency...

8.1
Introduction
8.2
Constraint Types
8.3
Expressing Hard Constraints in the Optimization Statement
8.4
Expressing Soft Constraints in the Optimization Statement
8.5
Equality Constraints
8.6
Takeaway
Exercises
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