Imbalanced rock burst assessment using variational autoencoder-enhanced gradient boosting algorithms and explainability

We conducted a study to evaluate the potential and robustness of gradient boosting algorithms in rock burst assessment, established a variational autoencoder (VAE) to address the imbalance rock burst dataset, and proposed a multilevel explainable artificial intelligence (XAI) tailored for tree-based...

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Bibliographic Details
Main Authors: Shan Lin, Zenglong Liang, Miao Dong, Hongwei Guo, Hong Zheng
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-08-01
Series:Underground Space
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2467967424000060