Method and device for constructing soil heavy metal environmental risk prediction model

Abstract

The invention discloses a method and device for constructing a soil heavy metal environmental risk prediction model in the field of heavy metal prediction. The method comprises the steps of measuringthe content of the heavy metal of the sample soil, and obtaining the heavy metal content data of the sample soil; carrying out spectral measurement and pretreatment on the sample soil to obtain a spectral reflectance curve of the treated sample soil; according to the heavy metal content data of the sample soil and the spectral reflectance curve of the processed sample soil, carrying out spectral transformation and characteristic waveband selection processing, and obtaining a characteristic waveband of the sample soil; constructing a BP-RBF neural network model; inputting the sample soil and the special waveband in the constructed BP-RBF neural network model for training and learning until the BP-RBF neural network model is converged. The construction device comprises a processor and a memory, the BP-RBF neural network is better in accuracy and higher in convergence speed, the precision of the soil heavy metal environment risk prediction is improved, and a new way is provided for the soil heavy metal environment risk prediction.

Description

technical field [0001] The invention relates to the technical field of heavy metal prediction, in particular to a method and device for constructing a soil heavy metal environmental risk prediction model. Background technique [0002] Soil is the most important natural resource for agricultural production. With the development of intensive agricultural production and the acceleration of urbanization, heavy metals enter the soil through sewage irrigation, atmospheric dry and wet deposition, and agricultural sludge. Heavy metal pollution has become the most polluted and most harmful environment in soil pollution today. one of the problems. To solve the problem of soil heavy metal pollution, we first need to find out the pollution situation. In May 2016, the State Council issued the "Soil Pollution Prevention and Control Action Plan" and proposed to find out the area and distribution of soil pollution before the end of 2018. Because hyperspectral remote sensing technology can...

AI Technical Summary

Problems solved by technology

Among them, the BP neural network technology is relatively mature and widely used in the detection and prediction of heavy metal content, showing the advantages of self-organizing adaptability, associative ability, fuzzy reasoning ability and self-learning ability, but it needs a long training time and the system training is not enough. Stable, sometimes converged to local minimum and other deficiencies, there is a certain deviation

Images