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Journal of Automation and Information Sciences
SJR: 0.232 SNIP: 0.464 CiteScore™: 0.27

ISSN Imprimer: 1064-2315
ISSN En ligne: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v40.i3.30
pages 23-34

Robust Modeling by Experimental Data Using Polynomial Iteration GMDH Algorithm

Tatyana I. Aksenova
Zhozef Fourier University, Grenoble, France

RÉSUMÉ

The polynomial iteration algorithm to realize the robust parametric and structural estimation within the frame of GMDH technique is presented. The two-level neural network structure with the controlled model complexity provides the computational stability of GMDH-PNN algorithm. The computational experiment demonstrating the parametric and structural robustness in the presence of outliers as well as examples of modeling problems solution in pharmacology and medicine are described.


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