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Journal of Automation and Information Sciences

Erscheint 12 Ausgaben pro Jahr

ISSN Druckformat: 1064-2315

ISSN Online: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

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Study of Efficiency of Fuzzy GMDH with Different Forms of Partial Descriptions and Adaptation Algorithms in Prognosis Problems

Volumen 40, Ausgabe 4, 2008, pp. 62-74
DOI: 10.1615/JAutomatInfScien.v40.i4.50
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ABSTRAKT

We study the fuzzy group method of data handling (GMDH), which enables one to derive fuzzy prognosis models under indeterminacy conditions. Experimental investigations of efficiency of the suggested FGMDH with partial descriptions in the form of quadric polynomials, Chebyshev, Laguerre and Fourier orthogonal polynomials are performed. We also tested efficiency and application of different adaptation methods of prognosis models. A comparative analysis with the classic GMDH and the Back Propagation neural network is performed.

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