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Ensemble stacking rockburst prediction model based on Yeo–Johnson, K-means SMOTE, and optimal rockburst feature dimension determination
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 determination are use...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468028/ https://www.ncbi.nlm.nih.gov/pubmed/36097043 http://dx.doi.org/10.1038/s41598-022-19669-5 |