A two-level hybrid evolutionary algorithm for modeling
one-dimensional dynamic systems by higher-order ODE
models
H. Cao, L. Kang, T. Guo, Y. Chen, and H. de Garis. 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.
%0 Journal Article
%1 cao:2000:ode2GP
%A Cao, Hong-Qing
%A Kang, Li-Shan
%A Guo, Tao
%A Chen, Yu-Ping
%A de Garis, Hugo
%D 2000
%J IEEE Transactions on Systems, Man and Cybernetics --
Part B: Cybernetics
%K ODE THEMA, algorithm, algorithms, computation, crossover differential dynamic equation, evolutionary genetic hybrid modeling models, one-dimensional operator ordinary programming, systems, two-level
%N 2
%P 351--357
%T A two-level hybrid evolutionary algorithm for modeling
one-dimensional dynamic systems by higher-order ODE
models
%U http://ieeexplore.ieee.org/iel5/3477/18067/00836383.pdf
%V 40
%X 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.
@article{cao:2000:ode2GP,
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.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Cao, Hong-Qing and Kang, Li-Shan and Guo, Tao and Chen, Yu-Ping and {de Garis}, Hugo},
biburl = {https://www.bibsonomy.org/bibtex/2c1ec904e4b2599058ebb909a3f55c759/brazovayeye},
interhash = {a0fae444fab651d352be9774a0cae8f7},
intrahash = {c1ec904e4b2599058ebb909a3f55c759},
issn = {1083-4419},
journal = {IEEE Transactions on Systems, Man and Cybernetics --
Part B: Cybernetics},
keywords = {ODE THEMA, algorithm, algorithms, computation, crossover differential dynamic equation, evolutionary genetic hybrid modeling models, one-dimensional operator ordinary programming, systems, two-level},
month = {April},
number = 2,
pages = {351--357},
size = {7 pages},
timestamp = {2008-06-19T17:37:19.000+0200},
title = {A two-level hybrid evolutionary algorithm for modeling
one-dimensional dynamic systems by higher-order {ODE}
models},
url = {http://ieeexplore.ieee.org/iel5/3477/18067/00836383.pdf},
volume = 40,
year = 2000
}