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The Application of Improved BP Neural Network Algorithm in Urban Air Quality Prediction: Evidence from China

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2 Author(s)
Qing Chen ; Sch. of Comput. Sci. & Technol., Wuhan Inst. of Technol., Wuhan ; Yuxiang Shao

According to the limitations of traditional BP neural network algorithm, the method of adding momentum factor and changing learning rate is used to improve the traditional BP neural network algorithm and establish the new model of BP neural network which is applied to the urban air quality prediction. Practical application shows that improved BP neural network algorithm overcome the shortcomings like slow convergence speed, bad generation ability and easily falling into local minimum values. The model established for urban air quality prediction has characteristics of representative and predicting ability so that it has a broad application prospect in future urban air quality assessment.

Published in:

Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on  (Volume:2 )

Date of Conference:

19-20 Dec. 2008

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