Artificial intelligence improving safety and risk analysis: A comparative analysis for critical infrastructure

A. Guzman, S. Ishida, E. Choi, A. Aoyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Recently, the sustainability of traditional technologies employed in critical infrastructure brings a serious challenge for our society. In order to make decisions related with safety of critical infrastructure, the values of accidental risk are becoming relevant points for discussion. However the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and deal with high amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI). Therefore, this paper aims to investigate and compare AI algorithms for risk assessment. These algorithms are classified mainly into Expert Systems, Artificial Neural Networks and Hybrid intelligent Systems. This paper explains the principles of each classification system, as well as its applications in safety. Lately, this paper performs a comparative analysis of three representative techniques, such as Fuzzy-Expert System, Neural Networks, and Adaptive Neuro Fuzzy Inference System.

Original languageEnglish
Title of host publication2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016
PublisherIEEE Computer Society
Pages471-475
Number of pages5
ISBN (Electronic)9781509036653
DOIs
Publication statusPublished - 2016 Dec 27
Externally publishedYes
Event2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016 - Bali, Indonesia
Duration: 2016 Dec 42016 Dec 7

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2016-December
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016
CountryIndonesia
CityBali
Period16/12/416/12/7

Keywords

  • ANFIS
  • Artificial Intelligence
  • Risk Assessment
  • Safety

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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