Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy

A Dynamic Adaptive Failure Detection Algorithm based on Grey System Theory

Authors
Daosheng Mu, Haoming Wang, Lijuan Gao
Corresponding Author
Daosheng Mu
Available Online July 2015.
DOI
10.2991/icismme-15.2015.277How to use a DOI?
Keywords
Grey System; Adaptive; PULL; Failure detection.
Abstract

As an important part of disaster emergency response technology, failure detection technology is the foundation of the whole disaster emergency system. In this paper, an adaptive heartbeat detection mechanism GTFD based on grey system theory is studied, with the general armament department test message system as the background. The reliability and real-time of detection mechanism are improved by prediction of failure probability of occurrence and warning which based on a small amount of message on the system monitoring.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
Series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
978-94-62520-67-7
ISSN
1951-6851
DOI
10.2991/icismme-15.2015.277How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Daosheng Mu
AU  - Haoming Wang
AU  - Lijuan Gao
PY  - 2015/07
DA  - 2015/07
TI  - A Dynamic Adaptive Failure Detection Algorithm based on Grey System Theory
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 1288
EP  - 1293
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.277
DO  - 10.2991/icismme-15.2015.277
ID  - Mu2015/07
ER  -