本发明属于地质灾害预测技术领域，具体涉及一种堆积层滑坡位移预测模型及预测方法。具体为，先通过CEEMDAN分解算法将滑坡累计位移分解成本征模态分量和残余趋势项，紧接着利用fine to corase方法将IMFs重构成高频和低频分量，再通过小波降噪算法对高频分量进行降噪处理，然后将去噪后的高频和低频分量合成周期分量，最后使用LSTM神经网络分别对趋势分量和周期分量进行预测，两者的预测结果相加即为预测的累计位移。本文使用提出的模型对三峡库区的八字门滑坡进行了研究和预测。结果显示，所提出的模型，预测精度更高，这对位滑坡预测带来了新的解决方案。
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