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Please use this identifier to cite or link to this item: http://ea.donntu.org/handle/123456789/8894

Title: Синтез аппроксимирующей функции при неизвестной структуре модели
Other Titles: Synthesis of the approximating function in case of the unknown structure of the model
Authors: Иващенко, Алеся Борисовна
Беловодский, Валерий Николаевич
Ivashchenko, A.B.
Belovodskiy, V.N.
Keywords: approximation
the bank of functions
the least squares method
regression
perspective function
elimination
аппроксимирующая функция
структура модели
регрессия
устранение
Issue Date: 2011
Citation: Системный анализ и информационные технологии в науках о природе и обществе (САИТ-2011). Выпуск 1 – Донецк: ДонНТУ, – 2011. – 214 с.
Abstract: Ivashchenko A.B., Belovodskiy V.N. “Synthesis of the approximating function in case of the unknown structure of the model”. In this paper an effective technique of synthesis of approximating function, especially in case of unknown structure of model is presented. The algorithm stages are described, namely: formation of bank of functions, selection of perspective functions and elimination of the useless one. The paper discusses the features of software implementation and results of the algorithm testing. As a result of the technique analysis its advantages and disadvantages have been identified. Suggestions on improving of the methodology are offered.
URI: http://ea.donntu.edu.ua/handle/123456789/8894
Appears in Collections:№1(1)'2011

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