An Air Quality Predictive Model of Licang of Qingdao City Based on BP Neural Network

Abstract:

In order to obtain high precision results of urban air quality forecast, we propose a short-term predictive model of air quality in this paper, which is on the basis of the ambient air quality monitoring data and relevant meteorological data of a monitoring site in Licang district of Qingdao city in recent three years. The predictive model is based on BP neural network and used to predict the ambient air quality in the next some day or within a certain period of hours. In the design of the predictive model, we apply LM algorithm, Simulated Annealing algorithm and Early Stopping algorithm into BP network, and use a reasonable method to extract the historical data of two years as the training samples, which are the main reasons why the prediction results are better both in speed and in accuracy. And when predicting within a certain period of hours, we also adopt an average and equivalent idea to reduce the error accuracy, which brings us good results.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 3366-3371
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.3366
• Online since: September 2013
• Authors: Ruo Bo Xin, Zhi Fang Jiang, Ning Li, Lu Jian Hou
• Keywords: Air Quality, BP Neural Network (BPNN), Prediction

References

[1] Q. Chen and Y.X. Shao, The Application of Improved BP Neural Network Algorithm in Urban Air Quality Prediction: Evidence in China, " Pacific-Asia Workshop on Computational Intelligence and Industrial Application (PACIIA , 08), Dec. 2008, pp.160-163.

DOI: 10.1109/paciia.2008.401

[2] A.Z. Wang and D.B. Li, BP Neural Network and Its Application to the Forecast of the Air Quality Based on the MATLAB, Journal of Safety and Environment, Vol. 09, No. 02, pp.84-88, April (2007).

[3] C.L. Zhu, Z.F. Jiang and Q. Wang, Forecast Model of Environment Air Quality Based on B-P Neural Network, Computer Engineering and Applications, Vol. 43, NO. 22, pp.223-227, (2007).

[4] X.J. Zhou, X.H. Su and M.Y. Yuan, Forecast of Air Pollution Index Based on BP Neural Network, Journal of HARBIN Institute of Technology, Vol. 36, No. 05, pp.582-585, May (2004).

[5] Q.H. Zhang, R. Yao, W.N. Deng and G.R. Wang, PM10 Pollution and Its BP Neural Network Forecast Model, " Journal of XI, AN University of Science and Technology, Vol. 30, No. 01, pp.43-62, Jan. (2010).

[6] X. Qin, L. Lei and X.L. Yao, Methods to Improve the Generalization of BP Neural Network Applied in Air Pollution Forecast, Journal of Beijing University of Technology, Vol. 33, No. 08, pp.849-852, Aug. (2007).

[7] Z.F. Jiang, B.Q. Mao and X.X. M et al. , An Air Quality Forecast Model Based on the BP Neural Network of the Samples Self-Organization Clustering, 2010 Sixth International Conference on Natural Computation (ICNC 2010), Aug. 2010, p.1523–1527.

DOI: 10.1109/icnc.2010.5582643

[8] Z.Z. Shi, Neural NetWorks. Beijing: Higher Education Press, (2009).