Ensemble model for risk status evaluation of excavation

Song Shun Lin, Shui Long Shen, Annan Zhou, Ning Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)

Abstract

This study develops a risk status evaluation model by integrating the technique for order preference by similarity to an ideal solution (TOPSIS) and Monte Carlo simulation (MCS) methods. The excavation system is divided into subsystems based on the monitoring scheme. The TOPSIS method integrates the information on the influential factors, and MCS overcomes the uncertainty, fuzziness, and human errors in data collection. A comprehensive weight determination method is proposed to determine the weights of the influential factors. The developed model was applied to evaluate the risk status of excavation projects in Tianjin. The results were consistent with the actual conditions of the excavation system. The higher correlation factors in the evaluation results can be identified through correlation analysis. Finally, a value for the ideal parameter λ in the membership function is recommended through sensitivity analysis. The developed model provides guidelines for establishing early risk warnings and management for excavation engineering.

Original languageEnglish
Article number103943
JournalAutomation in Construction
Volume132
DOIs
Publication statusPublished - Dec 2021
Externally publishedYes

Keywords

  • Excavation system
  • Monte Carlo simulation
  • Risk status evaluation
  • TOPSIS method

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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