基于人工神经网络的公路软基沉降预测模型
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TU447

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上海市教委科技发展基金资助项目(01F03)


Prediction model of settlement of embankment on soft ground based on artificial neural network
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    摘要:

    基于人工神经网络理论,提出了根据前期沉降观测资料进行沉降预测的人工神经网络模型,并用于汕汾高速公路预压荷载却荷时间预报、研究表明,所建议的模型较传统沉降预测模型具有显著的优越性,应用前景广阔。

    Abstract:

    The magnitude of the post-construction settlement is the key element subjected to design and construction of embankment on soft ground. The observational method based on field measurement has higher prediction accuracy and has become a more effective settlement prediction method. A new settlement prediction model is presented based on neural network theory in the paper. The case studies show the accordance of the predicted settlements by the proposed model with the measured data. The model has wide application foreground in expressway construction.

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杨涛,李国维,樊琨.基于人工神经网络的公路软基沉降预测模型[J].上海理工大学学报,2003,(2):117-120.

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  • 最后修改日期:2003-01-02
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