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Author (up) Binxu Zhai; Jianguo Chen pdf 
  Title Research on the forecasting of Air Quality Index (AQI) based on FS-GA-BPNN: A case study of Beijing, China Type Conference Article
  Year 2017 Publication Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal ISCRAM 2017  
  Volume Issue Pages 307-321  
  Keywords Feature Selection; Genetic Algorithm; Backpropagation Neural Network; Air Quality Index; forecasting  
  Abstract The analysis and forecasting of eminent air quality play a significant role in municipal regulatory planning and emergency preparedness. In this paper, a FS-GA-BPNN model forecasting the daily average Air Quality Index (AQI) is proposed. Special procedures for feature extraction to find more potential significant variables and feature selection to remove redundant information and avoid overfitting are conducted before modelling. Three different models BPNN, GA-BPNN and FS-GA-BPNN are established to compare the prediction accuracy, generalization ability and reliability. 17 parameters involving pollutant concentration, meteorological elements and surrounding factors are found essential for the method effectiveness. The result shows that the FS-GA-BPNN model generally performs superior to ordinary BPNN, suggesting the necessity of extensive data mining and feature extraction for successful machine learning. The results of this paper can help to conduct air quality pre-warning system and improve the emergency planning process of extreme weather events.  
  Address Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing, China  
  Corporate Author Thesis  
  Publisher Place of Publication Albi, France Editor Tina Comes, Frédérick Bénaben, Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN Medium  
  Track Planning, Foresight and Risk analysis Expedition Conference 14th International Conference on Information Systems for Crisis Response And Management  
  Notes Approved no  
  Call Number Serial 1466  
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