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dc.date2017
dc.date.accessioned2025-08-22T12:18:00Z-
dc.date.available2025-08-22T12:18:00Z-
dc.date.issued2017
dc.identifier.identifierDspace\SGAU\20170522\64062
dc.identifier.citationDanilenko A.N. Neural network prediction model of the pilots’ errors // Сборник трудов III международной конференции и молодежной школы «Информационные технологии и нанотехнологии» (ИТНТ-2017) - Самара: Новая техника, 2017. - С. 1519-1522.
dc.identifier.urihttp://repo.ssau.ru/jspui/handle/123456789/13648-
dc.description.abstractThis paper introduces a hybrid model of the neuro-fuzzy classifier with integrated prediction of pilots’ mistakes. Experiments and studies of the network were conducted on real and test samples.The upgraded hybrid neuro-fuzzy classifier structure and the learning algorithm can solve the problem of the need for multiple individual performance measurements, the dynamics of which would make it possible to build a trend and solve the problem on small samples. Used in organizational and management activities, this principle can help in predicting the danger caused by the human factor.
dc.languageen
dc.publisherНовая техника
dc.titleNeural network prediction model of the pilots’ errors
dc.typeArticle
local.identifier.oldurihttp://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Neural-network-prediction-model-of-the-pilots’-errors-64062
local.identifier.oldurihttp://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Neural-network-prediction-model-of-the-pilots’-errors-64062
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