Journal of Automation and Information Sciences
Publicado 12 números por año
ISSN Imprimir: 1064-2315
ISSN En Línea: 2163-9337
SJR:
0.173
SNIP:
0.588
CiteScore™::
2
Indexed in
Study of Impact of Data Sampling Division upon the Accuracy of Simulation by the GMDH Algorithms
Volumen 40,
Edición 3, 2008,
pp. 35-46
DOI: 10.1615/JAutomatInfScien.v40.i3.40
SINOPSIS
Division of a sample and the criteria for the best division are important elements in GMDH algorithms. We consider the efficiency of sampling division in problems of approximation, extrapolation and forecasting. Main attention is paid to a quasioptimal method of division, which in combination with other methods is able to increase the accuracy of the extrapolation and forecasting. The highest accuracy of the models is achieved by joining a quasioptimal division and adaptive prediction. The use of multiple methods of division allows to choose appropriate technology for each problem according to the particular object one.
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