Evolutionary Modeling of Systems of Ordinary
Differential Equations with Genetic Programming
Genetic Programming and Evolvable Machines, 1 (4):
309--337 (October 2000)DOI: doi:10.1023/A:1010013106294
Abstract
This paper describes an approach to the evolutionary
modeling problem of ordinary differential equations
including systems of ordinary differential equations
and higher-order differential equations. Hybrid
evolutionary modeling algorithms are presented to
implement the automatic modeling of one- and
multi-dimensional dynamic systems respectively. The
main idea of the method is to embed a genetic algorithm
in genetic programming where the latter is employed to
discover and optimize the structure of a model, while
the former is employed to optimize its parameters. A
number of practical examples are used to demonstrate
the effectiveness of the approach. Experimental results
show that the algorithm has some advantages over most
available modeling methods.
