基于文化算法的煤矿安全监测数据聚类分析

Clustering Analysis for Coal Mine Safety Monitoring Data Based on Cultural Algorithms

本文构造了一种新的模型来描述煤矿安全监测数据,克服了单纯使用数值表示的单一化,避免了采用语义描述的复杂冗余化。提出了SDFCM聚类算法,将新模型运用到聚类分析中,更准确的表示相似度,利用文化算法的全局搜索能力以及信仰空间中知识的引导,可以更好的分离出煤矿数据中高危数据。

This paper constructs a new model to describe coal mine safety monitoring data,which overcomes the simplification and avoids the complex and redundance of semantic description.The SDFCM is proposed.In this paper,the new model will be applied to clustering analysis,expressing the similarity exactly,using cultural algorithm＇s global search capability and leading the knowledge in belief space.It can isolate from the high-risk data from coal mine safety monitoring data.