Title
An Innovative Air Purification Method and Neural Network Algorithm Applied to Urban Streets
Abstract
AbstractIn 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.
Year
DOI
Venue
2019
10.4018/IJERTCS.2019100101
Periodicals
Field
DocType
Volume
Computer science,Real-time computing,Artificial neural network,Distributed computing
Journal
10
Issue
ISSN
Citations 
4
1947-3176
1
PageRank 
References 
Authors
0.37
0
3
Name
Order
Citations
PageRank
Meryeme Boumahdi110.37
Chaker El Amrani243.15
Siegfried Denys310.37