Prediction of Coal Spontaneous Combustion in Mine Based on Fuzzy C Means Clustering Algorithm

To realize the prediction control of coal spontaneous combustion in mine, we analyze the reasons and get a total of 6 kinds of factors including coal moisture content, calorific value, sulphur content, angle of inclination, geological structure and gas content of coal seam. Through data selection over the years in a mine, we classify the data by fuzzy C means clustering algorithm and build standard model base. We match the new data with model base by close degree of fuzzy pattern recognition method, predict spontaneous combustion degree of the mining coal seam, and choose a different mining scheme to control coal spontaneous combustion and ensure safety production according to different degree.