基于多头自注意力机制的LSTM-MH-SA滑坡位移预测模型研究

LSTM-MH-SA landslide displacement prediction model based on multi-head self-attention mechanism

受自身地质条件及外界周期、随机等因素影响,滑坡演变过程具有典型跃变特征。传统基于门控机制的深度学习模型对阶跃型滑坡预测能力不足,多头自注意力通过关注不同尺度时序数据的隐含信息能自适应挖掘序列的变化程度特征,有效学习数据潜在变化趋势,提升序列的预测能力。研究基于变分模态分解技术将滑坡累积位移量分解成趋势项、周期项和随机项,对各位移分量和影响因子开展动态时间规整相关性分析。结合多头自注意力机制和长短时记忆网络模型对各位移分量进行动态预测,各位移分量预测值相加得到实际预测结果。以三峡库区白水河滑坡作为研究区,对监测点ZG118开展累积位移预测,采用监测点ZG93、XD01进行模型适应性验证,试验结果表明对于降雨、库水位变化导致的阶跃数据段,新模型能大大提升预测的精度,为三峡库区滑坡位移预测研究提供新的思路。

Under the influences of the geological conditions of landslide and external periodic and random factors, the evolution process of the landslide has typical abrupt characteristics. The conventional deep learning model based on gating mechanism has insufficient ability to predict step mutation sequence, while by mining the potential information of time series data with different scales, multi-head self-attention can adaptively find the alteration trend of sequences and improve the prediction ability of landslide sequence. Based on variational mode decomposition, the cumulative displacement of landslide was decomposed into trend displacement, periodic displacement and stochastic displacement. Dynamic time warping algorithm was used to analyze the correlation between each component and influencing factors. These displacement components were dynamically predicted by a modified model integrated with long short-term memory(LSTM) neural network and multi-head self-attention mechanism, and the predicted values of each component were added to obtain the cumulative displacement prediction result. The monitoring point ZG118of Baishuihe landslide in the Three Gorges Reservoir area was taken as an example to predict the cumulative displacement in this paper. The monitoring points ZG93 and XD01 were used for model adaptability verification. The results show that the new model can greatly improve the prediction accuracy for the step data mutation caused by the changes of rainfall and reservoir water level,providing a new idea for the prediction of landslide displacement in the Three Gorges Reservoir area.