Structure identification of NN-ANARX model by genetic algorithm with combined cross-correlation-test based evaluation function

Author

Nõmm, Sven ; Vassiljeva, Kristina ; Belikov, Juri ; Petlenkov, Eduard

Author_Institution

Control Syst. Dept., Tallinn Univ. of Technol., Tallinn, Estonia

fYear

2011

fDate

19-21 Dec. 2011

Firstpage

65

Lastpage

70

Abstract

Application of genetic algorithm to determine structure of Neural Networks based Additive Nonlinear eXogenous (NN-ANARX) model and if possible to simplify the architecture of corresponding neural network constitutes subject of present paper. In this paper, we construct a specific fitness function, which depends on mean square error, certain cross correlation coefficients and an order of the model.

Keywords

correlation methods; genetic algorithms; neurocontrollers; nonlinear control systems; NN-ANARX model; combined cross-correlation-test based evaluation function; cross correlation coefficients; genetic algorithm; mean square error; neural networks based additive nonlinear eXogenous model; structure identification; Artificial neural networks; Biological cells; Computational modeling; Correlation; Genetic algorithms; Mathematical model; Mean square error methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation (ICCA), 2011 9th IEEE International Conference on

Conference_Location

Santiago

ISSN

1948-3449

Print_ISBN

978-1-4577-1475-7

Type

conf

DOI

10.1109/ICCA.2011.6137961

Filename

6137961