奇异谱分析在地铁沉降预测中的应用

地铁沉降受诸多因素干扰,其监测数据往往表现出非平稳、非线性特征.因此,首先利用奇异谱分析(SSA)方法提取监测数据的趋势项和周期成分,以削弱噪声、提高数据信噪比;然后利用BP神经网络分别对趋势序列与周期序列进行预测并重构,进而得到预测值.实验结果表明,相较于BP神经网络模型,SSA_BP神经网络模型的整体预测精度更高、...

Application of Singular Spectrum Analysis in the Prediction of Subway Settlement

Subway settlement is disturbed by many factors,and its monitoring data often show non-stationary and nonlinear characteristics.In this paper,we used the singular spectrum analysis(SSA)method to extract the trend sequence and period sequence of monitoring data,in order to reduce the noise and improve the signal-to-noise ratio.Then,we used BP neural network to predict and reconstruct the trend sequence and period sequence respectively.Finally,we obtained the predicted value.The experimental results show that the prediction accuracy of SSA_BP neural network model is higher than that of BP neural network model,and the maximum prediction length of SSA_BP neural network model is better.