Prediction model for spontaneous combustion temperature of coal based on PSO-XGBoost algorithm
Abstract The construction of a predictive model that accurately reflects the spontaneous combustion temperature of coal in goaf is fundamental to monitoring and early warning systems for thermodynamic disasters, including coal spontaneous combustion and gas explosions. In this paper, on the basis of...
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Main Authors: | Hui Zhuo, Tongren Li, Wei Lu, Qingsong Zhang, Lingyun Ji, Jinliang Li |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
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Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-87035-2 |
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