Air Quality Prediction of Pollution Sources Based on Wavelet Neural Network

DOI

10.2991/eeeis-17.2017.45How to use a DOI?

Keywords

wavelet neural network, pollution source, air quality, forecasting.

Abstract

In order to realize the prediction of air quality of pollution sources, this paper uses the method of wavelet neural network. In this paper, the pollutant concentration values of pollution sources were predicted, so as to realize the monitoring and early warning of pollution source emission. In this paper, the main chemical plants in Taizhou city are selected as the research object. The wavelet neural network is used to forecast the concentration of sulfur dioxide, nitrogen oxide of the chemical plant emissions. Finally, the experiments show that the wavelet neural network is useful to forecast the concentration of pollution sources.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Hong-Da JI
AU  - Li YANG
AU  - Yan-Feng WANG
AU  - Xiu-Bin DAI
AU  - Jun WANG
PY  - 2017/09
DA  - 2017/09
TI  - Air Quality Prediction of Pollution Sources Based on Wavelet Neural Network
BT  - Proceedings of the 3rd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2017)
PB  - Atlantis Press
SP  - 324
EP  - 328
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-17.2017.45
DO  - 10.2991/eeeis-17.2017.45
ID  - JI2017/09
ER  -