A comparison of neural network, evidential reasoning and multiple regression analysis in modelling bridge risks

Ying Ming Wang*, Taha M. S. Elhag

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

164 Citations (Scopus)

Abstract

Artificial neural network (ANN), the evidential reasoning (ER) approach and multiple regression analysis (MRA) can all be utilized to model bridge risks, but their modelling mechanisms and performances are quite different and therefore need comparison. This study compares the modelling mechanisms of the three alternative approaches and their performances in modelling a set of bridge risk data. It is found that ANN outperforms the ER approach and MRA for the considered case study. The reason for this is analyzed. The advantages and disadvantages of the three alternative approaches are also compared.

Original languageEnglish
Pages (from-to)336-348
Number of pages13
JournalExpert Systems with Applications
Volume32
Issue number2
DOIs
Publication statusPublished - Feb 2007

Keywords

  • Artificial neural network
  • Bridge risk assessment
  • Multiple regression analysis
  • Performance measurement
  • The evidential reasoning approach

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence

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