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A New Method for Pore Pressure Prediction on Malfunctioning Cells Using Artificial Neural Networks

机译:一种使用人工神经网络孔隙压力预测的一种新方法

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摘要

Embankment rockfill dams are the most common dam construction types used in the world today. One third of all embankment dam failures are caused by dam slope instability. The dam is stable when the slopes are stable. Slope safety of the dam is assessed through pore and total pressure data analysis registered on pressure measurement cells installed in the dam. During the service life of a dam, one or more cells may malfunction after years of operation. Cell replacement implies economically unjustified high costs and is usually technically impossible and high risk. In this paper, the problem of a malfunctioning cell with a small available dataset is analysed. A new method for pore pressure prediction on malfunctioning cells has been developed using several successive artificial neural networks (ANNs) to obtain high accuracy of the predicted values. The results show that these predicted values are more precise than values we could have obtained using only one artificial neural network for prediction.
机译:堤防堆石坝是当今世界上使用的最常见的大坝施工类型。所有路堤故障中的三分之一是由大坝坡稳定性引起的。当斜坡稳定时,大坝稳定。通过在安装在大坝中安装的压力测量单元上注册的孔和总压力数据分析评估大坝的斜坡安全性。在大坝的使用寿命期间,经过多年的操作后,一个或多个小区可能发生故障。细胞更换意味着经济上不合解的高成本,通常是技术上不可能和高风险。本文分析了具有小型可用数据集的故障单元的问题。使用几个连续的人工神经网络(ANN)开发了一种新的孔隙压力预测方法,以获得预测值的高精度。结果表明,这些预测值比我们只使用一个人工神经网络用于预测所获得的值更精确。

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