基于提升小波和最小二乘支持向量机的大坝变形预测
首发时间:2011-01-10
摘要:本文提出了一种基于提升小波和最小二乘支持向量机的大坝变形预测方法,即通过提升小波分析提取大坝监测数据效应量,分别对各效应量使用最小二乘支持向量机模型进行训练预测,然后将各分量的预测结果合成,作为最终的变形预测结果。算例表明,该方法较符合实际情况,具有很高的预测精度和良好的泛化能力。
关键词: 大坝监测分析 提升小波 分量提取 最小二乘支持向量机
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Dam Deformation Prediction Based on Lifting Wavelet Least Square Support Vector Machine
Abstract:A model based on lifting wavelet and support vector machine for dam deformation prediction is presented. Firstly, through the lifting wavelet ,the effect size of dam monitoring data is analyzed and extracted . Then, using LS-SVM respectively, the amount of each effect size is trained to forecast. Finally, the predicted results of various components are synthesized to be used as the final prediction result of deformation. The calculation result shows that this method is more in accord with the actual situation, with high prediction accuracy and good generalization ability.
Keywords: dam monitoring and analysis lifting wavelet Least Square Support Vector Machine combination forecasting
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No.4403153481280129****
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