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

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

9 Citations (Scopus)

48 Downloads (CityUHK Scholars)

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	AIP Conference Proceedings
Publisher	AIP Publishing
Volume	1890
ISBN (Print)	978-0-7354-1568-3
DOIs	https://doi.org/10.1063/1.5005245
Publication status	Published - 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
Volume	1890
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Publisher's Copyright Statement

COPYRIGHT TERMS OF DEPOSITED FINAL PUBLISHED VERSION FILE: This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared inBaoping Cai, Min Xie, Yonghong Liu, Yiliu Liu, Renjie Ji, and Qiang Feng, "A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks", AIP Conference Proceedings 1890, 040043 (2017) and may be found at https://doi.org/10.1063/1.5005245.

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10.1063/1.5005245

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Cite this

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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",

year = "2017",

month = oct,

doi = "10.1063/1.5005245",

language = "English",

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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 AIP Conference Proceedings. vol. 1890, 040043, AIP Publishing, 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

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

Y1 - 2017/10

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

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85031101440&origin=recordpage

U2 - 10.1063/1.5005245

DO - 10.1063/1.5005245

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-0-7354-1568-3

VL - 1890

BT - AIP Conference Proceedings

PB - AIP Publishing

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

Abstract

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UN SDGs

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