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融合图卷积神经网络和注意力机制的PM2.5小时浓度多步预测 |
傅颖颖1,2, 张丰1,2, 杜震洪1,2, 刘仁义1,2 |
1.浙江大学 浙江省资源与环境信息系统重点实验室,浙江 杭州 310028 2.浙江大学 地理信息科学研究所, 浙江 杭州 310027 |
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Multi-step prediction of PM2.5 hourly concentration by fusing graph convolution neural network and attention mechanism |
FU Yingying1,2, ZHANG Feng1,2, DU Zhenhong1,2, LIU Renyi1,2 |
1.Zhejiang Provincial Key Lab of GIS, Zhejiang University, Hangzhou 310028, China 2.Department of Geographic Information Science, Zhejiang University, Hangzhou 310027, China |
引用本文:
傅颖颖, 张丰, 杜震洪, 刘仁义. 融合图卷积神经网络和注意力机制的PM2.5小时浓度多步预测[J]. 浙江大学学报(理学版), 2021, 48(1): 74-83.
FU Yingying, ZHANG Feng, DU Zhenhong, LIU Renyi. Multi-step prediction of PM2.5 hourly concentration by fusing graph convolution neural network and attention mechanism. Journal of Zhejiang University (Science Edition), 2021, 48(1): 74-83.
链接本文:
https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2021.01.011
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https://www.zjujournals.com/sci/CN/Y2021/V48/I1/74
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