DocumentCode :
1797440
Title :
A connectionist approach to airliner safety
Author :
Schneider, Marvin Oliver ; Garcia Rosa, Joao Luis
Author_Institution :
Dept. of Postgrad. Studies (Inf. Technol.), Senac Univ. Center, Sao Paulo, Brazil
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
4070
Lastpage :
4075
Abstract :
The present paper introduces the system SINCO-Flightsim, an intelligent hybrid symbolic connectionist approach for the treatment of emergency situations on commercial airliners, currently available as a computer simulation. The system´s main focus is on human failure, which accounts for a major part of accidents and incidents in airline traffic. The underlying architecture, using the biologically more plausible learning algorithm GeneRec and contrasting it to learning via back-propagation is presented. System modules are described as well as the learned data sets. In its first version, the system provides a series of typical sensors and means of interaction for treating emergency situations successfully. The respective results are outlined in this paper. We trust that the approach has the potential to contribute to airliner safety as it takes major stress factors off the pilots´ shoulders and helps treating emergency situations in a more objective manner.
Keywords :
aerospace accidents; air safety; air traffic; backpropagation; digital simulation; emergency management; human factors; occupational stress; travel industry; GeneRec; SINCO-Flightsim system; airline traffic accidents; airline traffic incidents; airliner safety; backpropagation; biologically more plausible learning algorithm; commercial airliners; computer simulation; emergency situations; human failure; intelligent hybrid symbolic connectionist approach; pilot; stress factors; Accidents; Aircraft; Computer crashes; Elevators; Meteorology; Sensors; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
Type :
conf
DOI :
10.1109/IJCNN.2014.6889455
Filename :
6889455
Link To Document :
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