A two-level hybrid evolutionary algorithm for modeling
one-dimensional dynamic systems by higher-order ODE
models
IEEE Transactions on Systems, Man and Cybernetics --
Part B: Cybernetics, 40 (2):
351--357 (April 2000)Abstract
This paper presents a new algorithm for modeling
one-dimensional (1-D) dynamic systems by higher-order
ordinary differential equation (HODE) models instead of
the ARMA models as used in traditional time series
analysis. A two-level hybrid evolutionary modeling
algorithm (THEMA) is used to approach the modeling
problem of HODE's for dynamic systems. The main idea of
this modeling algorithm is to embed a genetic algorithm
(GA) into genetic programming (GP), where GP is
employed to optimize the structure of a model (the
upper level), while a GA is employed to optimize the
parameters of the model (the lower level). In the GA,
we use a novel crossover operator based on a nonconvex
linear combination of multiple parents which works
efficiently and quickly in parameter optimization
tasks. Two practical examples of time series are used
to demonstrate the THEMA's effectiveness and
advantages.
