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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Imprimir: 1064-2315
ISSN On-line: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v44.i4.10
pages 1-12

Analytical and Numerical Study of the Selective Properties of the Errors Unbiasedness Criterion in the Problems of Inductive Modeling

Evgeniya A. Savchenko
International Research and Training Center of Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kyiv, Ukraine
Vladimir S. Stepashko
International Research and Training Center of Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

RESUMO

The selective properties of the error unbiasedness criterion and its relationship to the known GMDH criteria, including the classic solutions unbiasedness criterion, are studied. Theoretically, it is proved that the errors unbiasedness criterion is an adequate external GMDH criterion. The behavior of the minimum of this criterion for different levels of noise in the data was investigated numerically and it was shown that it possessed the noise immunity property.

Referências

  1. Ivakhnenko A.G., Stepashko V.S. , Simulation noise immunity.

  2. Ivakhnenko A.G., Savchenko Е.А., Ivakhnenko G.A. , The GMDH algorithm for choosing the optimal model by the external criterion of the error with the definition extension by the model bias and its use in committees and neural networks.

  3. Ivakhnenko A.G., Ivakhnenko G.A., Savchenko E.A., GMDH algorithm for optimal model choice by the external error criterion with the definition extension by model bias and its applications to the committees and neural networks.

  4. Ivakhnenko A.G., Savchenko E.A., Investigation of efficiency of additional determination method of the model selection in the modeling problems by application of GMDH algorithm.

  5. Savchenko E.A., Stepashko V.S. , The analysis of the selective properties of GMDH criteria while their successive application.

  6. Savchenko E.A., Stepashko V.S., Semina L.P. , Numerical study of the selective properties of the criterion of the errors unbiasedness.

  7. Stepashko V.S. , GMDH algorithms as a basis for automation of the modeling process by experimental data.

  8. Stepashko V.S. , Method of critical variances as analytical tool of theory of inductive modeling.

  9. Stepashko V.S. , Structural identification of predicting models in a planned experiment.


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