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首页> 外文期刊>Computers and Geotechnics >Ann-based Model For Predicting The Bearing Capacity Of Strip Footing On Multi-layered Cohesive Soil
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Ann-based Model For Predicting The Bearing Capacity Of Strip Footing On Multi-layered Cohesive Soil

机译：基于Ann的多层粘性土上条形基础承载力预测模型

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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.
机译：实际上，立足点最有可能建立在多层土壤上。现有的预测4层至10层粘性土承载力的方法不准确。本文旨在开发一种基于多重回归方法和多层感知器（MLP）（一种类型的人工神经网络）的更准确的承载力预测方法。从开发的多元回归模型和MLP中以易处理的方程形式获得了承载力预测，并将其与使用传统方法预测的值进行了比较。结果表明，人工神经网络能够准确预测带状基础的承载力，并且性能优于现有方法。

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