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Author Boumahdi, M.; El Amrani, C.; Denys, S. pdf  url
doi  openurl
  Title An innovative air purification method and neural network algorithm applied to urban streets Type A1 Journal article
  Year (down) 2019 Publication International journal of embedded and real-time communication systems Abbreviated Journal  
  Volume 10 Issue 4 Pages 1-19  
  Keywords A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL)  
  Abstract In the present work, multiphysics modeling was used to investigate the feasibility of a photocatalysis-based outdoor air purifying solution that could be used in high polluted streets, especially street canyons. The article focuses on the use of a semi-active photocatalysis in the surfaces of the street as a solution to remove anthropogenic pollutants from the air. The solution is based on lamellae arranged horizontally on the wall of the street, coated with a photocatalyst (TiO2), lightened with UV light, with a dimension of 8 cm × 48 cm × 1 m. Fans were used in the system to create airflow. A high purification percentage was obtained. An artificial neural network (ANN) was used to predict the optimal purification method based on previous simulations, to design purification strategies considering the energy cost. The ANN was used to forecast the amount of purified with a feed-forward neural network and a backpropagation algorithm to train the model.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos Publication Date 2019-09-20  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-5225-7199-5 ISBN Additional Links UA library record  
  Impact Factor Times cited Open Access  
  Notes Approved no  
  Call Number UA @ admin @ c:irua:162595 Serial 8103  
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