摘要
针对环境监测中,难以实时在线处理海量颗粒物数据的问题,提出了一种基于实时技术的大气颗粒物在线分析系统,实现了颗粒物统计、浓度变化、来源解析等功能.该系统利用实时数据库来实时采集、存储海量大气数据,解决了环境监测中数据的海量问题;同时,引入自适应共振神经网络算法和逻辑回归模型进行数据分析,成功降低数据规模,提升数据分析速度.实践表明,该在线分析系统能在合理时间内得到准确的分析结果,具有重要的实际意义.
For environmental monitoring, the existing online analysis system is difficult to deal with massive atmospheric particle data. In this paper, we propose an atmospheric particle online analysis system based on real-time technologies, which aims to achieve atmospheric particle statistics, concentration change and the source analysis. The system adopts real-time databases to realize real-time capturing, stores massive atmospheric particle data, and solves the massive data problem in environmental monitoring. Besides, to accelerate data analysis and reduce data scale, the system adopts the ART-2a neural network algorithm and logistic regression model. The experiment results prove that the online analysis system could get accurate analysis result within a reasonable time. Besides, the experiment demonstrates the practical significance of our system.
出处
《计算机系统应用》
2017年第1期101-105,共5页
Computer Systems & Applications
基金
国家水体污染控制与治理科技重大专项(2012ZX07505003)
关键词
实时技术
海量数据
聚类分析
在线分析
环境监测
real-time technology
massive data
clustering analysis
online analysis
environmental monitoring
