Ensemble stacking rockburst prediction model based on Yeo–Johnson, K-means SMOTE, and optimal rockburst feature dimension determination

Ensemble stacking rockburst prediction model based on Yeo–Johnson, K-means SMOTE, and optimal rockburst feature dimension determination

Abstract Rockburst forecasting plays a crucial role in prevention and control of rockburst disaster. To improve the accuracy of rockburst prediction at the data structure and algorithm levels, the Yeo–Johnson transform, K-means SMOTE oversampling, and optimal rockburst feature dimension determinatio...

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Bibliographic Details
Main Authors: Lijun Sun, Nanyan Hu, Yicheng Ye, Wenkan Tan, Menglong Wu, Xianhua Wang, Zhaoyun Huang
Format: Article
Language:English
Published: Nature Portfolio 2022-09-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-19669-5

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https://doi.org/10.1038/s41598-022-19669-5

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