大数据混合结构的电炉企业公共突发事件危机预警系统

Public Emergency Crisis Warning System of Electric Furnace Enterprises with Big Data Mixed Structure

为解决电炉企业公共突发事件危机预警系统的分类能力差、预警误报累积分布比例高的问题,研究大数据混合结构的电炉企业公共突发事件危机预警系统。采用C/S结构、B/S结构和大数据数据库相结合的大数据混合结构,构建新的系统结构,从而设计系统功能模块,通过决策树算法分类事件,实现电炉企业公共突发事件危机预警。结果表明,该方法准确分类了事件样本,并且预警误报累积分布比例数值在2.0%以下,数值未发生较大波动,证实了其提高了事件分类能力和降低了预警误报累积分布比例,从而提高了危机预警性能,具备更高的应用价值。

In order to solve the problems of poor classification ability and high cumulative distribution of early warning false alarms in the public emergency crisis early warning system of electric furnace enterprises,a big data hybrid structure of electric furnace enterprise public emergency crisis early warning system is studied.A new system structure is constructed by adopting the big data mixed structure combining C/S structure,B/S structure and big data database,so as to design the system function module,classify the events by decision tree algorithm,and realize the public emergency crisis warning of electric furnace enterprises.The results show that this method accurately classifies event samples,and the cumulative distribution ratio of early warning false positives is below 2.0%,and the value does not fluctuate significantly,which proves that it improves the event classification ability and reduces the cumulative distribution ratio of early warning false positives,thus improving the crisis warning performance,and has higher application value.