基于改进DBScan算法的雷暴挖掘与研究

为了从已发生的雷电现象中提取雷暴并研究雷暴活动规律。文中根据雷电定位系统采集的雷电数据,使用大数据、数据挖掘等计算机技术,开发基于Spark框架的改进DBScan算法,进行雷电聚类分析,提取雷暴,在ArcGIS软件中动态分析雷暴产生、爆发、移动、消亡全过程,最后通过计算机对雷暴进行分析统计,寻找雷暴活动规律。根据历史雷电数据逆向挖掘雷暴,掌握雷暴的活动规律,对今后雷暴预警奠定基础。

Excavation and Research of Thunderstorm Based on Improved DBScan Algorithm

In order to extract thunderstorms from existing lightning phenomena and study thunderstorm activity law, based on the lightning data collected by the lightning location system, this paper develops an improved DBScan algo rithm based on Spark framework, carries out lightning clustering analysis, extracts thunderstorms, dynamically analyzes the whole process of thunderstorms' occurrence, outbreak, movement and extinction in ArcGIS software, and finally checks them by computer. Thunderstorms are analyzed statistically to find thunderstorm activity rules. According to the historical thunderstorm data, the thunderstorm is excavated in reverse, and the thunderstorm activity law is mastered, which lay a foundation for thunderstorm early warning in the future.