Research on Coal and Gas Outburst Prediction and Sensitivity Analysis Based on an Interpretable Ali Baba and the Forty Thieves–Transformer–Support Vector Machine Model

Research on Coal and Gas Outburst Prediction and Sensitivity Analysis Based on an Interpretable Ali Baba and the Forty Thieves–Transformer–Support Vector Machine Model

Coal and gas outbursts pose significant threats to underground personnel, making the development of accurate prediction models crucial for reducing casualties. By addressing the challenges of highly nonlinear relationships among predictive parameters, poor interpretability of models, and limited sam...

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Bibliographische Detailangaben
Hauptverfasser: Yanping Wang, Zhixin Qin, Zhenguo Yan, Jun Deng, Yuxin Huang, Longcheng Zhang, Yuqi Cao, Yiyang Wang
Format: Artikel
Sprache:English
Veröffentlicht: MDPI AG 2025-01-01
Schriftenreihe:Fire
Schlagworte:
transformer-based feature extraction
classification assessment methods
interpretable model
SHAP analysis
permutation feature importance
Online Zugang:https://www.mdpi.com/2571-6255/8/2/37

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https://www.mdpi.com/2571-6255/8/2/37

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