Granger-Causality Mining in Atmospheric Visibility Based on Deep Learning

  • Bo Liu
  • Xi HeEmail author
  • Jianqiang Li
  • Guangzhi Qu
  • Jianlei Lang
  • Rentao Gu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 551)


Causal relationship mining of multi-dimensional meteorological time series data can reveal the potential connection between visibility and other influencing factors, and it is meaningful in terms of environmental management, air pollution chasing, and haze control. However, because causality analysis based on statistical methods or traditional machine learning techniques cannot represent the complex relationship between visibility and its influencing factors, as an extension of traditional Granger-causality analysis, we propose a causality mining method based on the seq2seq-LSTM deep learning model. The method can profoundly reveal the hidden relationship between different features and visibility and the regular pattern of bad weather, which can provide theoretical support for air pollution control.


Granger-causality Deep learning Multidimensional time series 



This work is supported by National Natural Science Foundation of China (61702021), Beijing Natural Science Foundation (4174082), and General Program of Science and Technology Plans of Beijing Education Committee (SQKM201710005021).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Bo Liu
    • 1
  • Xi He
    • 1
    Email author
  • Jianqiang Li
    • 1
  • Guangzhi Qu
    • 2
  • Jianlei Lang
    • 3
  • Rentao Gu
    • 4
  1. 1.Faculty of Information Technology, School of Software EngineeringBeijing University of TechnologyBeijingChina
  2. 2.Computer Science and Engineering DepartmentOakland UniversityRochesterUSA
  3. 3.Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy EngineeringBeijing University of TechnologyBeijingChina
  4. 4.Beijing Laboratory of Advanced Information Networks, School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijingChina

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