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

被引：135

作者：

Wang, Ying-Ming

Elhag, Taha M. S.

机构：

[1] Univ Manchester, Sch Mech Aerosp & Civil Engn, Manchester M60 1QD, Lancs, England

[2] Fuzhou Univ, Sch Publ Adm, Fuzhou 350002, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2007年 / 32卷 / 02期

基金：

英国工程与自然科学研究理事会;

关键词：

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

D O I：

10.1016/j.eswa.2005.11.029

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：336 / 348

页数：13

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