农业面源污染监测及预警系统设计
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摘要
农业面源污染是导致地表水污染的主要原因。为解决农业面源污染监控中遇到的瓶颈问题,设计并实现了一套基于信息融合、物联网及云计算技术的农业面源污染监测及预警系统。目前系统运行平稳,预测预警准确性较高,较好地实现了对农业面源污染的动态监测、跟踪与预警。
Agricultural non-point source pollution is the main cause of surface water pollution. To solve the bottleneck problem in agricultural non-point source pollution monitoring, an agricultural non-point source pollution monitoring and warning system was designed and implemented based on information fusion, internet of things and cloud computing technology. At present, the system runs with smooth working and relatively high forecasting accuracy. It can better realize the dynamic monitoring, tracking and early warning of agricultural non-point source.
Agricultural non-point source pollution is the main cause of surface water pollution. To solve the bottleneck problem in agricultural non-point source pollution monitoring, an agricultural non-point source pollution monitoring and warning system was designed and implemented based on information fusion, internet of things and cloud computing technology. At present, the system runs with smooth working and relatively high forecasting accuracy. It can better realize the dynamic monitoring, tracking and early warning of agricultural non-point source.
引文
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[2]冯晓娜,张刚,王咏.农业面源污染防治措施进展研究[J].环境科学与管理,2017,42(8):89-93.
[3]彭力.物联网技术概论(第2版)[M].北京:北京航空航天大学出版社,2015.
[4]Cortes C,Vapnik V.Support vector networks[J].Machine Learning,1995,20(3):273-297.
[5]Huang G B,Zhu Q Y,Siew C K.Extreme learning machine theory and applications[J].Neurocomputing,2006,70(1-3)489-501.
[6]毛力,宋益春,李引,等.Research of Improved Fuzzy c-means Algorithm Based on a New Metric Norm[J].上海交通大学学报(英文版),2015,20(1):51-55.
[7]Li Mao,Lidong Zhang,Xingyang Liu,Chaofeng Li,Hong Yang.Improved Extreme Learning Machine and Its Application in Image Quality Assessment[J].MATHEMATICALPROBLEMS IN ENGINEERING,2014:7.