The Environmental Quality Evaluation Based on BP Neural Network and PSO and Case Study

Author

Zhou, Xiaoguo ; Zhang, Wenzhong ; Yuan, Wei ; Liu, Qingchao

Author_Institution

Sch. of Archit. & Ocean Eng., Jiangsu Uiversity of Sci. & Technol., Zhenjiang

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

32

Lastpage

35

Abstract

Using particle swarm optimization (PSO) to optimize BP neural network model is proposed in this paper. The new model is more quickly and accurate. The basic idea of this model is: Firstly PSO is used to optimize the BP neural network´s initialized weights, an optimized result is got; then based on the optimized result the BP neural network is used for further optimization. We can use this model for the environmental quality evaluation of Qinhuangdao Port regional. Finally we can get exactly appraise, this can be direct the environmental protection.

Keywords

backpropagation; environmental science computing; neural nets; particle swarm optimisation; quality management; BP neural network; PSO; Qinhuangdao Port regional; environmental protection; environmental quality evaluation; particle swarm optimization; Artificial neural networks; Cities and towns; Environmental economics; Feedforward neural networks; Intelligent networks; Marine technology; Monitoring; Neural networks; Neurons; Particle swarm optimization; BP neural network; PSO; environmental quality evaluation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3505-0

Type

conf

DOI

10.1109/IITA.Workshops.2008.49

Filename

4731874