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Electronic archive of Tomsk Polytechnic University
Article . 2015
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Нейросетевой метод подкрепляемого обучения в задачах автоматического управления

descriptionPublicationkeyboard_double_arrow_right Article 20 Nov 2015 Russian Federation Russian Publisher:Томский политехнический университет

Нейросетевой метод подкрепляемого обучения в задачах автоматического управления

Abstract

Рассмотрен метод построения адаптивных систем управления, в основе функционирования которых лежит метод обучения с подкреплением. Описано программное средство для моделирования и исследования таких систем управления. Предложен способ применения искусственных нейронных сетей для представления функции оценки воздействия.

Country
Russian Federation
Related Organizations
Keywords

адаптивные системы управления, программные средства, обучение, искусственные сети, воздействия, функционирование, автоматическое управление, нейросетевые методы, задачи

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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).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Average
Powered by OpenAIRE graph
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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