Decision-supporting models for human-reliability based safety promotion in offshore Liquid Natural Gas terminal

Renyou Zhang (Corresponding Author), Henry Tan

Research output: Contribution to journalArticle

Abstract

Offshore LNG terminal is a place which contains many high-risk operations. Although many protection instruments have been installed to guarantee the safety in offshore LNG terminal, many accidents still happen. Through the investigation of the accidents, people gradually realise that humans dominate the operational safety in offshore LNG terminal. Therefore, people need a human-reliability based decision-making model to make better plans for avoiding human errors. However, there is limited effort for reaching this requirement, so the particular research should be conducted. This study aims to separately introduce some learning algorithms such as neural networks and K-Nearest Neighbours (KNN) into the construction of the human-reliability based decision-supporting models. All these decision-supporting models will be based on the reality in the Beihai Offshore LNG Terminal. Then, the most robust model will be decided by the Mean Square Error (MSE) and the Average Error (AE) of each model.
Original languageEnglish
Pages (from-to)83-98
Number of pages15
JournalSafety and Reliability
Volume38
Issue number1-2
Early online date19 Feb 2019
DOIs
Publication statusPublished - 2019

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Natural gas
Liquefied natural gas
Liquids
Accidents
Mean square error
Learning algorithms
Decision making
Neural networks

Keywords

  • offhsore LNG terminal
  • human-reliability based
  • decision-supporting

Cite this

Decision-supporting models for human-reliability based safety promotion in offshore Liquid Natural Gas terminal. / Zhang, Renyou (Corresponding Author); Tan, Henry.

In: Safety and Reliability, Vol. 38, No. 1-2, 2019, p. 83-98.

Research output: Contribution to journalArticle

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