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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

Synthesis Method of Empirical Models Optimal by Complexity under Uncertainty Conditions

Volumen 48, Edición 9, 2016, pp. 64-74
DOI: 10.1615/JAutomatInfScien.v48.i9.50
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SINOPSIS

There was developed the synthesis method of optimal complexity models for conditions when the model variables are fuzzy values. The method is oriented to the class of polynomial models. The best models are selected by using criteria of regularity or displacement. The application of ideas of genetic algorithms gives the opportunity to eliminate the problem of large dimension which is characteristic of combinatorial method. The efficiency of the developed method was verified on industrial data that allowed one to synthesize the empirical model optimal by structure for drilling conditions.

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CITADO POR
  1. Gorbiychuk Mikhail, Bila Olga, Humeniuk Taras, Zaiachuk Yaroslav, Development of a method for optimizing operation of centrifugal gas superchargers under conditions of uncertainty, Eastern-European Journal of Enterprise Technologies, 5, 4 (101), 2019. Crossref

  2. Горбійчук М. І., Кропивницький Д. Р., Числовий метод обчислення критичного навантаження на долото при бурінні свердловин, Automation of technological and business processes, 13, 1, 2021. Crossref

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