A two-level hybrid evolutionary algorithm for modeling one-dimensional dynamic systems by higher-order ODE models.
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.
Cao
H Q
HQ
State Key Lab. of Software Eng., Wuhan Univ.
Kang
L S
LS
Guo
T
T
Chen
Y P
YP
de Garis
H
H