首页|基于FEEMD-GRU-FC模型的滑坡位移预测

基于FEEMD-GRU-FC模型的滑坡位移预测

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
水库库区滑坡同时受到降雨和水库水位周期性变化的影响,这会干扰滑坡位移预测模型在该类区域的预测性能.为此,提出了一种针对环境周期性变化特点的FEEMD-GRU-FC(Fast Ensemble Empirical Mode Decomposition-Gated Recurrent Unit-Fully Connected Layer)滑坡位移预测模型.该模型充分考虑位移数据不同频率之间的噪声影响,将位移分解为不同频率的子序列分别预测,采用PCC(Pearson Correlation Coefficient)方法选择影响较大的外部环境因素,添加全连接层完善GRU模型提取环境数据中周期性变化特征的能力,模型结合三峡库区八字门滑坡的实际数据进行模拟仿真,使用不同预测模型和评价指标进行多角度对比验证.实验结果表明:所提模型在八字门滑坡的预测效果要优于其他3 种模型,其拟合度达到了98.6%,3 种不同误差指标均为最低,证明了该模型可以准确预测库区滑坡位移.研究成果可为防灾减灾工作提供指导.
Landslide displacement prediction based on FEEMD-GRU-FC model
Landslides in reservoir areas are affected by rainfall and periodic changes in reservoir water level,which will interfere with the prediction performance of landslide displacement prediction models.A FEEMD-GRU-FC(fast ensemble empirical mode decomposition-gated recurrent unit-fully connected layer)landslide displacement prediction model based on the periodic environmental changes was proposed.The model fully considered the influence of noise among different frequencies of displace-ment data,divided the displacement into sub-sequences of different frequencies to predict them respectively,and used the PCC(Pearson correlation coefficient)method to select external environmental factors with large influence.The ability of the GRU mod-el to extract periodic change features from environmental data was improved by adding a full connection layer.The model was ap-plied by combining with the actual data of the Bazimen Landslide in the Three Gorges Reservoir area.Different prediction models and evaluation indicators were used for multi-perspective comparison and verification.The experimental results showed that the model proposed was better than the other three models in predicting Bazimen Landslide displacement.Its fitting degree was 98.6%,and three kinds of error indexes were the lowest,which proved that the model can accurately predict the landslide dis-placement in the reservoir area.The research results can guide disaster prevention and reduction.

landslide displacement predictionPearson correlation coefficientgated recurrent unitfully connected layernonlinearityBazimen LandslideThree Gorges Reservoir area

何清、李丽琳、林子安

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广西交科集团有限公司科技信息部,广西 南宁 530000

桂林电子科技大学 计算机与信息安全学院,广西 桂林 541000

滑坡位移预测 皮尔逊相关系数 门控循环单元 全连接层 非线性 八字门滑坡 三峡库区

国家自然科学基金项目广西科技重大专项广西重点研发项目

U23A20280桂科AA23062038桂科AB21196041

2024

10.16232/j.cnki.1001-4179.2024.07.014

人民长江
水利部长江水利委员会

人民长江

CSTPCD北大核心
影响因子：0.451
ISSN：1001-4179
年,卷(期)：2024.55(7)
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