A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks

Baoping Cai; Min Xie; Yonghong Liu; Yiliu Liu; Renjie Ji; Qiang Feng

doi:10.1063/1.5005245

A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks

Baoping Cai^*
, Min Xie
, Yonghong Liu
, Yiliu Liu
, Renjie Ji
, Qiang Feng

^*Corresponding author for this work

School of Reliability and Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

The word resilience originally originates from the Latin word "resiliere", which means to "bounce back". The concept has been used in various fields, such as ecology, economics, psychology, and society, with different definitions. In the field of critical infrastructure, although some resilience metrics are proposed, they are totally different from each other, which are determined by the performances of the objects of evaluation. Here we bridge the gap by developing a universal critical infrastructure resilience metric from the perspective of reliability engineering. A dynamic Bayesian networks-based assessment approach is proposed to calculate the resilience value. A series, parallel and voting system is used to demonstrate the application of the developed resilience metric and assessment approach.

Original language	English
Title of host publication	2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017
Publisher	American Institute of Physics Inc.
ISBN (Electronic)	9780735415683
DOIs	https://doi.org/10.1063/1.5005245
State	Published - 5 Oct 2017
Event	2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017 - Hubei Province, China Duration: 27 Oct 2017 → 29 Oct 2017

Publication series

Name	AIP Conference Proceedings
Volume	1890
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017
Country/Territory	China
City	Hubei Province
Period	27/10/17 → 29/10/17

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10.1063/1.5005245

Cite this

Cai, B., Xie, M., Liu, Y., Liu, Y., Ji, R., & Feng, Q. (2017). A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks. In 2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017 Article 040043 (AIP Conference Proceedings; Vol. 1890). American Institute of Physics Inc.. https://doi.org/10.1063/1.5005245

@inproceedings{d86668cb16da41f1ad216f787bbddbc2,

title = "A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks",

abstract = "The word resilience originally originates from the Latin word {"}resiliere{"}, which means to {"}bounce back{"}. The concept has been used in various fields, such as ecology, economics, psychology, and society, with different definitions. In the field of critical infrastructure, although some resilience metrics are proposed, they are totally different from each other, which are determined by the performances of the objects of evaluation. Here we bridge the gap by developing a universal critical infrastructure resilience metric from the perspective of reliability engineering. A dynamic Bayesian networks-based assessment approach is proposed to calculate the resilience value. A series, parallel and voting system is used to demonstrate the application of the developed resilience metric and assessment approach.",

author = "Baoping Cai and Min Xie and Yonghong Liu and Yiliu Liu and Renjie Ji and Qiang Feng",

note = "Publisher Copyright: {\textcopyright} 2017 Author(s).; 2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017 ; Conference date: 27-10-2017 Through 29-10-2017",

year = "2017",

month = oct,

day = "5",

doi = "10.1063/1.5005245",

language = "英语",

series = "AIP Conference Proceedings",

publisher = "American Institute of Physics Inc.",

booktitle = "2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017",

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Cai, B, Xie, M, Liu, Y, Liu, Y, Ji, R & Feng, Q 2017, A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks. in 2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017., 040043, AIP Conference Proceedings, vol. 1890, American Institute of Physics Inc., 2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017, Hubei Province, China, 27/10/17. https://doi.org/10.1063/1.5005245

A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks. / Cai, Baoping; Xie, Min; Liu, Yonghong et al.
2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017. American Institute of Physics Inc., 2017. 040043 (AIP Conference Proceedings; Vol. 1890).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks

AU - Cai, Baoping

AU - Xie, Min

AU - Liu, Yonghong

AU - Liu, Yiliu

AU - Ji, Renjie

AU - Feng, Qiang

PY - 2017/10/5

Y1 - 2017/10/5

N2 - The word resilience originally originates from the Latin word "resiliere", which means to "bounce back". The concept has been used in various fields, such as ecology, economics, psychology, and society, with different definitions. In the field of critical infrastructure, although some resilience metrics are proposed, they are totally different from each other, which are determined by the performances of the objects of evaluation. Here we bridge the gap by developing a universal critical infrastructure resilience metric from the perspective of reliability engineering. A dynamic Bayesian networks-based assessment approach is proposed to calculate the resilience value. A series, parallel and voting system is used to demonstrate the application of the developed resilience metric and assessment approach.

AB - The word resilience originally originates from the Latin word "resiliere", which means to "bounce back". The concept has been used in various fields, such as ecology, economics, psychology, and society, with different definitions. In the field of critical infrastructure, although some resilience metrics are proposed, they are totally different from each other, which are determined by the performances of the objects of evaluation. Here we bridge the gap by developing a universal critical infrastructure resilience metric from the perspective of reliability engineering. A dynamic Bayesian networks-based assessment approach is proposed to calculate the resilience value. A series, parallel and voting system is used to demonstrate the application of the developed resilience metric and assessment approach.

UR - https://www.scopus.com/pages/publications/85031101440

U2 - 10.1063/1.5005245

DO - 10.1063/1.5005245

M3 - 会议稿件

AN - SCOPUS:85031101440

T3 - AIP Conference Proceedings

BT - 2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017

PB - American Institute of Physics Inc.

T2 - 2nd International Conference on Materials Science, Resource and Environmental Engineering, MSREE 2017

Y2 - 27 October 2017 through 29 October 2017

ER -

A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks

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