S8 Data - Landslide hazard early warning method for rock slopes using a hybrid LSTM-SARIMA data-driven model

S8 Data - <p>Landslide hazard early warning method for rock slopes using a hybrid LSTM-SARIMA data-driven model</p>

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Bibliographic Details
Main Author:	Yongxin Dai (13796385) (author)
Other Authors:	Zijian Li (339839) (author), Jingbiao Lu (21417505) (author)
Published:	2025
Subjects:	Biotechnology Inorganic Chemistry Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified support vector machine significant destructive power rock slopes using perform global denoising improved tangent angle introducing five data lstm )&# 8211 lstm &# 8211 comprehensive technical system original monitoring data monitoring data acquisition enabling accurate prediction pit mine slopes wavelet noise reduction stage technical system monitoring data analysis landslide warning criterion pit mine noise reduction effective monitoring system demonstrates landslide events prediction accuracy noise ratios based prediction hybrid lstm sarima data two rounds trend term term memory systematically researched svm ), sudden onset successful application sliding average random forest period term paper proposes major threat long short lightgbm ), largely focused intelligent algorithm influencing mechanisms human life full process focusing solely east china driven models driven model
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