Soil Quality Evaluation of Heavy Metal Pollution Based on BP Artificial Neural Network
Objective: To find a practical and simple method using artificial neural network for the soil quality assessment Methods: This paper introduces a BP neural network theory and method used in the soil evaluation of heavy metals pollution. And the authors designed the model of soil quality assessment based on BP neural network. Furthermore, the model was simulated and experiments were done extensively using MATLAB neural network toolbox. Through the simulation procedures, the evaluation of various levels of soil samples were gained and comparatively analyzed to difference assessment methods, such as Single Factor evaluation and Multiple Factor evaluation according to the rules of national environmental quality standards (GB15618-1995, China). Study Area: City Baotou and its suburbs. In here, the steel corporation was described as one of the biggest pollution source. There were totally 220 samples collected from soil measuring points. Conclusion: The useful BP neural network model can take advantages of simple network structure, fast convergence rate and strong generalization capability, and get good modeling effects for soil heavy metal pollution evaluation.
Soil pollutant Heavy Metal Pollution BP neural network
Xiang LI Xiaoyu ZHANG Hua LIU
Zhengzhou Institute of Aeronautical Industry Management Zhengzhou 450015, P.R. CHINA
国际会议
昆明
英文
393-397
2010-10-17（万方平台首次上网日期，不代表论文的发表时间）