Avionics system failure prediction based on bacteria evolution and gray neural network

Chaoqi Gu, Deyun Zhou, Xiaoyang Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aiming at the problem of the gray neural network easy to fall into local optimization, a failure prediction algorithm with bacterial evolutionary and gray neural network is proposed. First, a gray neural network fault detection model is established. Then, the bacterial evolutionary algorithm is selected to optimize the initial weights and thresholds of the network to solve the defect of network easy to fall into local optimization. Finally, several kinds of fault prediction effect of the algorithm are compared through the simulation experiment. The simulation results show that the algorithm combining bacterial evolutionary and gray neural network can achieve optimal prediction effect quickly.

Original languageEnglish
Title of host publicationProceedings of the First Symposium on Aviation Maintenance and Management
PublisherSpringer Verlag
Pages243-250
Number of pages8
EditionVOL. 1
ISBN (Print)9783642542350
DOIs
StatePublished - 2014
Event2013 1st Symposium on Aviation Maintenance and Management - Xi'an, China
Duration: 25 Nov 201328 Nov 2013

Publication series

NameLecture Notes in Electrical Engineering
NumberVOL. 1
Volume296 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference2013 1st Symposium on Aviation Maintenance and Management
Country/TerritoryChina
CityXi'an
Period25/11/1328/11/13

Keywords

  • Bacteria evolution
  • Fault diagnosis
  • Fault prediction
  • Neural network

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