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

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

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016
出版社IEEE Computer Society
ページ471-475
ページ数5
ISBN(電子版)9781509036653
DOI
出版ステータスPublished - 2016 12 27
外部発表はい
イベント2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016 - Bali, Indonesia
継続期間: 2016 12 42016 12 7

出版物シリーズ

名前IEEE International Conference on Industrial Engineering and Engineering Management
2016-December
ISSN(印刷版)2157-3611
ISSN(電子版)2157-362X

Conference

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

ASJC Scopus subject areas

  • ビジネス、管理および会計(その他)
  • 産業および生産工学
  • 安全性、リスク、信頼性、品質管理

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