Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning

被引：286

作者：

Kim, GH ^{[1
]}

An, SH ^{[1
]}

Kang, KI ^{[1
]}

机构：

[1] Korea Univ, Dept Agr Engn, Seoul 136701, South Korea

来源：

BUILDING AND ENVIRONMENT | 2004年 / 39卷 / 10期

关键词：

multiple regression analysis; neural networks; case-based reasoning; cost estimation;

D O I：

10.1016/j.buildenv.2004.02.013

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Adequate estimation of construction costs is a key factor in construction projects. This paper examines the performance of three cost estimation models. The examinations are based on multiple regression analysis (MRA), neural networks (NNs), and case-based reasoning (CBR) of the data of 530 historical costs. Although the best NN estimating model gave more accurate estimating results than either the MRA or the CBR estimating models, the CBR estimating model performed better than the NN estimating model with respect to long-term use, available information from result, and time versus accuracy tradeoffs. (C) 2004 Elsevier Ltd. All rights reserved.

引用

页码：1235 / 1242

页数：8

共 49 条

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