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| Analysis on typical PM2.5 and PM10 data based on MATLAB neural network |
| Zhang Dayong1,Zhang Xiang1,Chen Jun2 |
1. No. 94995 Unit,Rugao 226500;
2. No. 95631 Unit,Luzhou 646000 |
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Abstract Based on MATLAB toolbox,the analysis program of the BP neural network was built,and it was applied to evaluate PM2.5 and PM10. The three-layer BP neural network prediction system is constructed,and monthly data of two typical cities-Baoding and Lasa are used as training samples from October 2014 to January 2016. The prediction results of February and March in 2016 conform well to the published data. The study indicates that the analysis methods for PM2.5 and PM10 based on BP neural network are feasible and reasonable. And the results evaluation are objective and practical.
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Received: 21 March 2016
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| [1] |
陶俊,孙刚,徐康乐. 基于人工神经网络的缝翼凹槽填充降噪设计[J]. 空气动力学学报,2015,33(4):515-522.
|
| [2] |
李龙,魏靖,黎灿兵,等. 基于人工神经网络的负荷模型预测[J]. 电工技术学报,2015,30(8):225-230.
|
| [3] |
闫斌,戴公连,苏海霆. 基于气象参数的轨道板竖向温度梯度预测模型[J]. 华南理工大学学报(自然科学版),2014,42(12):9-13.
|
| [4] |
余世鹏,杨劲松,刘广明,等. 基于模糊神经算法的区域地下水盐分动态预测[J]. 农业工程学报,2014,30(18):142-150.
|
| [5] |
王岩,张友桃,胡鸿翔,等. 基于声发射和人工神经网络的混凝土损伤程度识别[J]. 建筑材料学报,2014,17(4):672-676.
|
| [6] |
朱大奇,史慧. 人工神经网络原理与应用[M]. 北京: 科学出版社,2006.
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2016, Vol. 33 
