Journal of Automation and Information Sciences
Выходит 12 номеров в год
ISSN Печать: 1064-2315
ISSN Онлайн: 2163-9337
SJR:
0.173
SNIP:
0.588
CiteScore™::
2
Indexed in
Study of Efficiency of Fuzzy GMDH with Different Forms of Partial Descriptions and Adaptation Algorithms in Prognosis Problems
Том 40,
Выпуск 4, 2008,
pp. 62-74
DOI: 10.1615/JAutomatInfScien.v40.i4.50
Краткое описание
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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