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Journal of Automation and Information Sciences

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ISSN Print: 1064-2315
ISSN Online: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v40.i4.50
pages 62-74

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

Yuriy P. Zaychenko
Institute of Applied Systems Analysis of National Technical University of Ukraine "Kiev Polytechnical Institute", Ukraine
Igor O. Zayets
Institute of Applied Systems Analysis of National Technical University of Ukraine "Kiev Polytechnical Institute", Ukraine

ABSTRACT

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.