"Three Zones"Division of Goaf Based on K-means Algorithm
The division of the"three zones"in goaf can effectively prevent coal spontaneous combustion.To further address the issue of differences in the division of coal spontaneous combustion"three zones"in different regions,this paper constructs a"three zone"division model for goaf based on the K-means algorithm.Based on the bundle data of the 3015 working face in Donghuantuo Coal Mine,a dataset was constructed.Three clustering algorithms and six clustering evaluation indicators were introduced to establish three"three belt"division models for goaf.The optimal clustering model was selected by analyzing the model's effectiveness.The results showed that the K-means model had the best clustering performance,with evaluation indica-tors such as contour coefficient,CH index,and DH index of 0.573,121.291,and 0.47,respectively.The results of the"three zones"division of goaf based on oxygen were 4.435-20.294 meters.The multi parameter,multi algorithm,and multi combina-tion coal spontaneous combustion goaf"three zone"division model constructed in this article has high accuracy and strong ap-plicability,and can be divided for different environments of coal spontaneous combustion three zones to ensure the safety of coal mining.
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