53 / 2021-11-15 10:50:09
Step-wise Landslide Displacement Prediction with Different Machine Learning Models in Bazimen Landslide
landslide displacement prediction,Three Gorges Reservoir,machine learning
全文待审
万祺 罗 / 中国地质大学(武汉)
锐 王 / 中国地质大学(武汉)
衍昊 郭 / 中国地质大学(武汉)
There is a complex nonlinear relationship between landslide influencing factors and landslide displacement, and predicting landslide displacement is helpful to study this nonlinear relationship. In the Three Gorges Reservoir Area, many landslides are affected by seasonal rainfall and periodic fluctuation of reservoir water level, and the displacement curve shows step-wise increase. Therefore, the landslide displacement can be decomposed into linearly increasing trend terms and fluctuating periodic terms. Bazimen landslide is a typical step-wise landslide in the Three Gorges Reservoir area, which is used to compare the accuracy of three machine learning methods. A polynomial function was used to predict trend displacement, and periodic displacement was predicted by using three machine learning models which were ASF-SVR, random forests, and gradient lifting trees. The RMSE of the three models is 28.11mm, 20.41mm, and 22.95mm respectively. The results show that the prediction effect of random forest is the best.





 
重要日期
  • 会议日期

    11月26日

    2021

    11月28日

    2021

  • 11月23日 2021

    初稿截稿日期

  • 11月30日 2021

    报告提交截止日期

  • 11月30日 2021

    注册截止日期

主办单位
国家自然科学基金委员会地球科学学部
国际工程地质与环境协会(IAEG)
中国地质大学(武汉)
湖北省巴东县人民政府
承办单位
湖北三峡库区地质灾害国家野外科学观测研究站
湖北省巴东人民政府
中国地质大学(武汉)工程学院
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