山西农业大学学报（自然科学版）2017，Vol.37Issue(5)：340-344,5.
环境监测中多传感器数据融合研究
Research on multi-sensor data fusion in environment monitoring
摘要
Abstract
[Objective] For the problem of low accuracy and reliability of single sensor data in environment monitoring,the paper proposed that based on the WSN monitoring system use an improved self-adaptive weighted fusion algorithm and fuzzy neural network to increase the reliability of environment monitoring.[Methods] Based on the data collected by multi sensors in the same period,applied the self-adaptive weighted algorithm improved by Euclidean distance and correlation function on the data fusion of homogeneous sensors,we designed a fuzzy neural network to translate the data from heterogeneous sensor into environment quality grade.[Results] The simulation experiment showed that the accuracy of the proposed homogeneous sensor data fusion algorithm was higher than some other kinds of algorithms,the fuzzy neural network algorithm could correctly classify 96 ％ verification samples after learning 350 training samples and the prediction curve could roughly match the real outputs.[Conclusion] The proposed homogeneous sensor data fusion algorithm increased the accuracy of data fusion,and the heterogeneous sensor data fusion algorithm could give a relatively reliable evaluation to overall environment quality.关键词
环境监测/多传感器/数据融合/欧式距离/模糊神经网络Key words
Environment monitoring/Multi sensor/Data fusion/Euclidean distance/Fuzzy neural network分类
矿业与冶金引用本文复制引用
刘静,李富忠,荆瑞俊..环境监测中多传感器数据融合研究[J].山西农业大学学报（自然科学版）,2017,37(5):340-344,5.基金项目
山西农业大学科技创新基金(2016004) （2016004）
