Including the feature of appropriate adjacent sites improves the PM2.5 concentration prediction with long short-term memory neural network model

被引：0
|
作者：
Mengfan, Teng [1 ]
Siwei, Li [1 ,2 ]
ge, Song [1 ]
jie, Yang [1 ,2 ]
Lechao, Dong [1 ]
hao, Lin [1 ]
Senlin, Hu [1 ]
机构：
[1] School of Remote Sensing and Information Engineering, Wuhan University, Wuhan,430079, China
[2] State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan,430079, China
来源：
Sustainable Cities and Society | 2022年 / 76卷
关键词：
Engineering Village;
D O I：
103427
中图分类号：
学科分类号：
摘要：
Adjacent sites - Appropriate adjacent site - Concentration prediction - Convolutional neural network - Hybrid model - Long short-term memory neural network - Neural network model - Neural-networks - PM 2.5 - Policy makers
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