Data Processing Method of Mine Wind Speed Monitoring Based on an Improved Fuzzy C-Means Clustering Algorithm

Analyzing and processing mine wind speed monitoring data is the key to realizing intelligent ventilation real-time calculation of network. According characteristics artificial regulation a system, local regression fuzzy C clustering algorithm proposed in this paper, which combines outlier with global air volume state analysis. Firstly, uses robust weighted principle analyze preprocess locally, determines risk degree abnormal according identified times outliers, number validity function, analyzes fluctuation results. The results show that most outliers are preprocessing. Still, dense weak, related window width setting weighting multiple. clusters can represent pre-processed cluster centers 4.4% lower than original because higher average data. law balance, pave way for deduction speed. There an implicit relationship between preprocessing process, when intensive not eliminated, they may be as separate clusters. research paper points out direction analysis, provide theoretical basis