A New PM2.5 Air Pollution Forecasting Model Based on Data Mining and BP Neural Network Model

DOI

10.2991/cimns-18.2018.25How to use a DOI?

Keywords

PM2.5 air pollution forecasting; BP neural network; Data mining; Meteorological data

Abstract

A new PM2.5 air pollution forecasting model based on data mining and BP neural network model was established in this paper. This model combined data mining and BP neural network algorithm with data of mass concentration of PM2.5 and meteorological data obtained from the Ministry of Original data Environmental Protection in China and Anhui Meteorological Data Service Center. The test results showed that the new PM2.5 air pollution forecasting model had higher prediction accuracy than before.

Copyright

© 2018, 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/).

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TY  - CONF
AU  - Anna Li
AU  - Xiao Xu
PY  - 2018/11
DA  - 2018/11
TI  - A New PM2.5 Air Pollution Forecasting Model Based on Data Mining and BP Neural Network Model
BT  - Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018)
PB  - Atlantis Press
SP  - 110
EP  - 113
SN  - 2352-538X
UR  - https://doi.org/10.2991/cimns-18.2018.25
DO  - 10.2991/cimns-18.2018.25
ID  - Li2018/11
ER  -