Aircraft equipment modeling using neural networks

Author

Svobodová, J. ; Koudelka, V. ; Raida, Z.

Author_Institution

Dept. of Radio Electron., Brno Univ. of Technol., Brno, Czech Republic

fYear

2011

fDate

12-16 Sept. 2011

Firstpage

627

Lastpage

630

Abstract

In this paper, the neural network module for simulating the behavior of an arbitrary system is described. The black-box modeling tool is aimed to simulate unknown systems characterized by measurements. The tool is able to model systems that cannot be described analytically due to their nonlinearity or complexity. Neural networks are suitable for solving real EMC problems leading to extremely high computation demands or to complicated experimental measurements. There are two main limitations: the sparsity of numerical results (due to the computation complexity) and the noise corrupting the measurement results. It is essential to find an equivalent model approximating the behavior of investigated system if the sparse or noisy data are available.

Keywords

aircraft; neural nets; EMC problem; aircraft equipment modeling; arbitrary system; behavior simulation; black-box modeling tool; computation complexity; neural network; noisy data; Aircraft; Atmospheric modeling; Neural networks; Noise measurement; Signal to noise ratio; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Electromagnetics in Advanced Applications (ICEAA), 2011 International Conference on

Conference_Location

Torino

Print_ISBN

978-1-61284-976-8

Type

conf

DOI

10.1109/ICEAA.2011.6046412

Filename

6046412