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Electronic archive of Tomsk Polytechnic University
Article . 2015
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Построение и исследование алгоритма поиска первой крайней подсистемы для заданной совместной системы линейных неравенств

descriptionPublicationkeyboard_double_arrow_right Article 20 Nov 2015 Russian Publisher:Томский политехнический университет

Построение и исследование алгоритма поиска первой крайней подсистемы для заданной совместной системы линейных неравенств

Abstract

Разработан алгоритм поиска крайней подсистемы для заданной системы линейных неравенств, определена область допустимых значений для этой подсистемы и предложен метод нахождения зависимых неравенств. Алгоритм включает учет возможных ограничений-равенств, а также приведение матрицы системы неравенств к матрице полного столбцового ранга. Работа алгоритма демонстрируется на тестовом примере.

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Keywords

крайние подсистемы, системы линейных неравенств, области допустимых значений, учет, зависимые неравенства, ограничения-равенства

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    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).
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    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.
    		 Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Average
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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
Green