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author:

Wang, Ying-Ming (Wang, Ying-Ming.) [1] (Scholars:王应明) | Elhag, Taha M. S. (Elhag, Taha M. S..) [2]

Indexed by:

EI Scopus SCIE

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. (C) 2005 Elsevier Ltd. All rights reserved.

Keyword:

artificial neural network bridge risk assessment multiple regression analysis performance measurement the evidential reasoning approach

Community:

  • [ 1 ] Univ Manchester, Sch Mech Aerosp & Civil Engn, Manchester M60 1QD, Lancs, England
  • [ 2 ] Fuzhou Univ, Sch Publ Adm, Fuzhou 350002, Peoples R China

Reprint 's Address:

  • 王应明

    [Wang, Ying-Ming]Univ Manchester, Sch Mech Aerosp & Civil Engn, POB 88, Manchester M60 1QD, Lancs, England

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Source :

EXPERT SYSTEMS WITH APPLICATIONS

ISSN: 0957-4174

Year: 2007

Issue: 2

Volume: 32

Page: 336-348

1 . 1 7 7

JCR@2007

7 . 5 0 0

JCR@2023

ESI Discipline: ENGINEERING;

JCR Journal Grade:1

Cited Count:

WoS CC Cited Count: 136

SCOPUS Cited Count: 158

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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