ANN-based model for predicting the bearing capacity of strip footing on multi-layered cohesive soil

被引：124

作者：

Kuo, Y. L. ^{[1
]}

Jaksa, M. B. ^{[1
]}

Lyamin, A. V. ^{[2
]}

Kaggwa, W. S. ^{[1
]}

机构：

[1] Univ Adelaide, Sch Civil Environm & Min Engn, Adelaide, SA 5005, Australia

[2] Univ Newcastle, Dept Civil Surveying & Environm Engn, Callaghan, NSW 2308, Australia

来源：

COMPUTERS AND GEOTECHNICS | 2009年 / 36卷 / 03期

关键词：

Bearing capacity; Cohesive soil; Limit analysis; Multilayered cohesive material; Strip footing; Neural network; NETWORKS;

D O I：

10.1016/j.compgeo.2008.07.002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In reality, footings are most likely to be founded on multi-layered soils. The existing methods for predicting the bearing capacity of 4-layer up to 10-layer cohesive soil are inaccurate. This paper aims to develop a more accurate bearing capacity prediction method based on multiple regression methods and multilayer perceptrons (MLPs), one type of artificial neural networks (ANNs). Predictions of bearing capacity from the developed multiple regression models and MLP in tractable equations form are obtained and compared with the value predicted using traditional methods. The results indicate ANNs are able to predict accurately the bearing capacity of strip footing and outperform the existing methods. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：503 / 516

页数：14

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