Artificial neural networks to updrafts localization and forecasting

Ivan Suzdalev

Doctoral dissertation

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Description

The dissertation examines the thermal flow detection and prediction problems during an  autonomous aircraft flight. The main research object is the thermal flows and artificial neural networks. Thermal flows are a very important  source for improving autonomous aircraft flight parameters, such as flight time and duration.

The primary aim of the dissertation is to create methodologies and algorithms to detect, identify and to successfully predict the parameters the thermal flows. The application are of the methods and algorithms developed is autonomous aircraft control system synthesis, research on mesoscale meteorological phenomena and synthesis of computing systems using  biological models.

The following objectives are carried out: thermal flow sensing using aircraft navigational parameters measurement data, thermal flow simulation modeling and data input necessary for modeling.

On the topic of the dissertation  6 articles have been published - one in the collection of articles included in the Thomson ISI, two - in conference proceedings, reviewed in Thomson ISI database, two - in Inspec database, cited journal, three - in reviewed international conference proceedings and one - in a national conference materials. 9 presentations of the topic of the dissertation have been given in conferences.

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DOI: https://doi.org/10.20334/2090-M

Book details

Data sheet

Year:
2012
ISBN:
978-609-457-392-7
Imprint No:
2090-M
Dimensions:
145×205 mm
Pages:
121 p.
Cover:
Softcover
Language:
Lithuanian
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