Multivariate adaptive regression (MARS) and hinged hyperplanes (HHP) for doweled pavement performance modeling

被引:54
作者
Attoh-Okine, Nii O. [1 ]
Cooger, Ken [2 ]
Mensah, Stephen [1 ]
机构
[1] Univ Delaware, Dept Civil Engn, Newark, DE 19716 USA
[2] Peak Consulting, Conifer, CO 80433 USA
关键词
Multivariate adaptive regression (MARS); Hinged hyperplanes (HHPO); Pavement performance modeling;
D O I
10.1016/j.conbuildmat.2009.04.010
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Standard neural networks in infrastructure performance modeling cannot handle discontinuities in the input training data set, and the performance can in some cases be an issue in the presence of higher frequency and higher order non linearity in pavement condition, traffic and other environmental data. This makes the traditional neural network more of a "black box" with limited physical explanation of the results. This paper is a comparative analysis between multivariate adaptive regression and hinged hyperplanes for doweled pavement performance modeling. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3020 / 3023
页数:4
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