Abstract
In recent years, applied researchers have become
increasingly interested in Adaptive Search (AS),
techniques such as the Genetic Algorithm (GA), and
Genetic Programming GP, for engineering design. This
paper illustrates the effectiveness of the genetic
programming paradigm for simple fluid systems
identification problems. The objective of the paper is
to establish methods for systems identification using
GP and sets of empirical data. The manipulation and
optimisation of these approximate functions that
describe the physical process is achieved using the GP
approach and by the development of complementary AS
techniques. Two new GP operators are introduced, the
first searches through possible values of terminals for
a particular functional tree structure, and the second
uses functional induction to improve the performance of
the technique.
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