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Структурная идентификация сложных объектов управления на базе методов кусочной аппроксимации

Структурная идентификация сложных объектов управления на базе методов кусочной аппроксимации

Abstract

The problem of complex object functioning model development is solved with the aid of algorithms of structure-ranging analysis and piecewise approximation. Two approaches to the solution are considered the first employs iterative algorithms which implement variational approach to piecewise approximation, while the second uses two-phase algorithms where the processes of input parameter space structuring and local regression model development are separated.

Решается задача построения модели функционирования сложного объекта с помощью алгоритмов структурно-классификационного анализа и кусочной аппроксимации. Предлагается два подхода к решению этой задачи при помощи итерационных алгоритмов, реализующих вариационный подход к задачам кусочной аппроксимации, и двухэтапных алгоритмов, в которых процессы структуризации пространства входных параметров и построения локальных регрессионных моделей разделены.

Keywords

КЛАССИФИКАЦИОННЫЙ АНАЛИЗ ДАННЫХ, СТРУКТУРНАЯ ИДЕНТИФИКАЦИЯ, КУСОЧНАЯ АППРОКСИМАЦИЯ СЛОЖНЫХ ЗАВИСИМОСТЕЙ, СТАТИСТИКА ФИШЕРА-ЧОУ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold