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

Airport functional damage assessment and prediction based on Bayesian network

Authors
Taoju Teng, Qingkun Yu, Feng Wang, Jianwu Wang
Corresponding Author
Taoju Teng
Available Online July 2015.
DOI
10.2991/icismme-15.2015.156How to use a DOI?
Keywords
airport; damage assessment; Bayesian network.
Abstract

After the enemy’ attack on the airport, how to assess the airport functional damage quickly and scientifically is an important link of the formation of combat effectiveness. This paper is based on the Bayesian theory, and establishes the functional damage and prediction model of airport. With an example of the calculation, the results show that a good simulation response. Under conditions of the regional high-tech war, the airport is the main target of the enemy attack. The damage effect of the airport directly affects the force balance between ourselves and the enemy, so the assessment of airport damage presents the striking study significance. Airport functional damage assessment and prediction refers to a comprehensive description, evaluation, and prediction about the airport system.

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-15.2015.156How 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  - Taoju Teng
AU  - Qingkun Yu
AU  - Feng Wang
AU  - Jianwu Wang
PY  - 2015/07
DA  - 2015/07
TI  - Airport functional damage assessment and prediction based on Bayesian network
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 751
EP  - 754
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.156
DO  - 10.2991/icismme-15.2015.156
ID  - Teng2015/07
ER  -