Research on Improved Strategy of Soil Heavy Metals based on Neural Network Model

Yiting Wang¹, Tingting Wang², Xiaolu Qiu³, Zhihong Ma⁴, Cuiping Zhao^4*

¹School of Agronomy and Resources Environment, Tianjin Agricultural University, Tianjin, 300384, China

²School of Computer and Information Engineering, Tianjin Agricultural University, Tianjin, 300384, China

³School of Economic and Management, Tianjin Agricultural University, Tianjin, 300384, China

⁴School of Basic Sciences, Tianjin Agricultural University, Tianjin, 300384, China

* Corresponding author

Abstract: Today, as the process of urban industrialization industrialization progresses, heavy metal pollution in large areas of soil in Beijing, trend is not encouraging, and hindering the process of urban development. To study how to improve soil conditions, In this paper, we used the mathematical modeling method, and using Principal Component Analysis Method and Neural Network Model. Results show: The pollution of heavy metals in urban soil has not improved. According to the specific situation of Beijing, we make the following recommendations: the focus of governance is on improving the removal rate of pollution in Hg and Cu, will effectively improve the condition of heavy metal pollution in soil. In this case, we use Matlab to verify the usefulness of the recommendations. The proposed changes have a reliable reference value for improving soil quality.

Keywords: Evaluation of heavy metal pollution in soil; Principal component analysis method; Neural network model; SPSS; MATLAB