APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKS

APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKS

The article considers the problems of mathematical approximation and analysis of flights on unmanned aerial vehicles with the help of neural mathematic models.

Bibliographic Details
Main Author: S. V. Korevanov
Format: Article
Language:Russian
Published: Moscow State Technical University of Civil Aviation 2016-11-01
Series:Naučnyj Vestnik MGTU GA
Subjects:
беспилотные летательные аппараты
траектория полета
нейросетевые системы
Online Access:https://avia.mstuca.ru/jour/article/view/522
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spelling doaj-f6701b1412814e819994441c374cd98e2021-07-28T21:00:33ZrusMoscow State Technical University of Civil Aviation Naučnyj Vestnik MGTU GA2079-06192542-01192016-11-01210135137522APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKSS. V. Korevanov0МГТУ ГАThe article considers the problems of mathematical approximation and analysis of flights on unmanned aerial vehicles with the help of neural mathematic models.https://avia.mstuca.ru/jour/article/view/522беспилотные летательные аппаратытраектория полетанейросетевые системы
collection DOAJ
language Russian
format Article
sources DOAJ
author S. V. Korevanov
spellingShingle S. V. Korevanov
APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKS
Naučnyj Vestnik MGTU GA
беспилотные летательные аппараты
траектория полета
нейросетевые системы
author_facet S. V. Korevanov
author_sort S. V. Korevanov
title APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKS
title_short APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKS
title_full APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKS
title_fullStr APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKS
title_full_unstemmed APPROXIMATION OF FLIGHT PATH LENGTH AND CONDITIONS UNMANNED AERIAL VEHICLES WITH NEURAL NETWORKS
title_sort approximation of flight path length and conditions unmanned aerial vehicles with neural networks
publisher Moscow State Technical University of Civil Aviation
series Naučnyj Vestnik MGTU GA
issn 2079-0619
2542-0119
publishDate 2016-11-01
description The article considers the problems of mathematical approximation and analysis of flights on unmanned aerial vehicles with the help of neural mathematic models.
topic беспилотные летательные аппараты
траектория полета
нейросетевые системы
url https://avia.mstuca.ru/jour/article/view/522
work_keys_str_mv AT svkorevanov approximationofflightpathlengthandconditionsunmannedaerialvehicleswithneuralnetworks
_version_ 1721263860615217152

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