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1. 南京理工大学电子工程与光学工程学院,江苏 南京 210094
2. 盐城工学院信息工程学院,江苏 盐城 224051
[ "刘燕(1986-),女,江苏盐城人,盐城工学院讲师,主要研究方向为数据处理、环境监测等。" ]
[ "张永平(1979-),男,河北邯郸人,博士,盐城工学院讲师,主要研究方向为大数据技术、压缩感知、物联网等。" ]
[ "朱成(1989-),男,江苏常州人,主要研究方向为物联网技术。" ]
[ "皋军(1971-),男,江苏盐城人,博士,盐城工学院教授,主要研究方向为人工智能、机器学习、模式识别等。" ]
[ "刘其明(1965-),男,江苏盐城人,硕士,盐城工学院副教授,主要研究方向为软件工程、算法流程与分析。" ]
网络出版日期:2017-11,
纸质出版日期:2017-11-25
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刘燕, 张永平, 朱成, 等. 基于大数据和物联网的空气质量预测监测研究[J]. 通信学报, 2017,38(Z2):129-138.
Yan LIU, Yong-ping ZHANG, Cheng ZHU, et al. Intelligent forecasting and monitoring of air index based on big data and internet of things[J]. Journal on communications, 2017, 38(Z2): 129-138.
刘燕, 张永平, 朱成, 等. 基于大数据和物联网的空气质量预测监测研究[J]. 通信学报, 2017,38(Z2):129-138. DOI: 10.11959/j.issn.1000-436x.2017266.
Yan LIU, Yong-ping ZHANG, Cheng ZHU, et al. Intelligent forecasting and monitoring of air index based on big data and internet of things[J]. Journal on communications, 2017, 38(Z2): 129-138. DOI: 10.11959/j.issn.1000-436x.2017266.
空气质量预监测已成为一种迫切需求,而这是一个复杂的系统工程。从基于大数据的智能决策角度研究智能空气指数预测,引入流行的分类算法,挖掘历史数据隐含的信息,实现空气质量预测;构建了基于物联网的空气质量监测系统,利用分类算法实现实时采集数据的智能处理。针对空气指数历史数据和实时采集数据规模较大的问题,为提高数据处理速度、增强空气质量预测的实时性,引入云计算技术加速数据处理;为使用户随时随地了解空气指数,还设计了基于Android平台开发空气指数预报客户端。
Air quality forecast has become an urgent need.However
numerical forecast of air quality is a complex systems engineering.The intelligent forecasting of air index was studied from the perspective of big data and intelligent decision making.For the index prediction of air quality
the popular classification algorithm was introduced to realize the intelligent analysis of historical data.To obtain air quality information in real time
a monitoring system based on Internet of Things was established
and intelligent processing of real-time data collected by the classification algorithm was achieved.Due to the large amount of historical air index data and real-time data collected
the technology of cloud computing and big data was introduced to speed up the data processing and improve the storage of data.In addition
the client based on Android was developed to allow users to query the air quality anytime
anywhere.
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