Prediction model for spontaneous combustion temperature of coal based on PSO-XGBoost algorithm

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Hui Zhuo, Tongren Li, Wei Lu, Qingsong Zhang, Lingyun Ji, Jinliang Li
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Coal spontaneous combustion
PSO-XGBoost model
Particle swarm optimization
Feature selection
Tenfold cross-validation
Online Access:https://doi.org/10.1038/s41598-025-87035-2
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-87035-2

Similar Items