Performance Evaluation of Hybrid PSO-BPNN-AdaBoost and PSO-BPNN-XGBoost Models for Rockburst Prediction with Imbalanced Datasets

Performance Evaluation of Hybrid PSO-BPNN-AdaBoost and PSO-BPNN-XGBoost Models for Rockburst Prediction with Imbalanced Datasets

The rockburst hazard is a primary geological disaster endangering the environment in underground engineering. Due to the complexity of the rockburst mechanism, traditional methods are insufficient to predict the rockburst hazard objectively, especially when dealing with an imbalanced dataset. To add...

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Bibliographic Details
Main Authors: Shujian Li, Pengpeng Lu, Weizhang Liang, Ying Chen, Qi Da
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
rockburst prediction
underground engineering
hybrid model
data preprocessing
machine learning
Online Access:https://www.mdpi.com/2076-3417/14/24/11792
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