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Prediction Methods to Determine Stability of Dam If There is Piping

机译:如果有管道,可以确定大坝稳定性的预测方法

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In the paper, mechanism for generation of piping in dam and key factors that affect the generation of piping are analyzed; eight measured indexes are selected as basis of prediction; such prediction methods as Distance Discriminant Analysis Model and SVM (Support Vector Machine) are established for piping in dam, meanwhile, contrastive analysis for the method has been carried out to neural network method. According to the study of twenty-three actual cases of piping projects in dam, it is showed that Distance Discriminant Method and SVM prediction model are with good performance. SVM that is based on neural network kernel function and Radial Basis Kernel Function has much higher prediction accuracy and SVM method is one effective method to solve issue of piping prediction in dam, which can be used in actual projects.
机译:在本文中,分析了水坝管道的机制和影响管道产生的关键因素;选择八个测量索引作为预测的基础;这种预测方法作为距离判别分析模型和SVM(支撑载体机器)在大坝中的管道建立,同时,对神经网络方法进行了对比的对比分析。根据对大坝管道项目二十三个实际情况的研究,表明距离判别方法和SVM预测模型具有良好的性能。基于神经网络内核功能和径向基础内核功能的SVM具有更高的预测精度,SVM方法是解决大坝管道预测问题的一种有效方法,可用于实际项目。

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