Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Sep 2:2022:9693175.
doi: 10.1155/2022/9693175. eCollection 2022.

Prediction Model of Soil Heavy Metal Content Based on Particle Swarm Algorithm Optimized Neural Network

Cuiqing Duan  1   2 , Baoqiang Wang  3 , Jinxiu Li  3
Affiliations

Prediction Model of Soil Heavy Metal Content Based on Particle Swarm Algorithm Optimized Neural Network

Cuiqing Duan et al. Comput Intell Neurosci. .

Abstract

In 2014, the relevant research data from the Ministry of Environmental Protection and the Ministry of Land and Resources showed that the total exceedance rate of soil heavy metal pollution in China had reached 16.1%, and in the construction of ecological civilization in the 13th Five-Year Plan, China has made the prevention and control of soil heavy metal pollution as the focus of prevention and control. Therefore, in this paper, four neural optimization network models, that is, radial basis neural network (RBFNN), generalized regression neural network (GRNN), wavelet neural network (WNN), and fuzzy neural network (FNN), are simulated and created to measure and correlate the soil heavy metal content in a city in northwest China and a city in central China from the actual situation in China. The simulations were conducted. Finally, by analyzing the comparison of predicted and true values of these four models on the test data of two sets of experimental data, the distribution of predicted differences to true values, and the calculation results of three error indicators, we found that WNN has the best prediction performance when using RBFNN, GRNN, WNN, and FNN for soil heavy metal content prediction.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Main types of heavy metals in soil.
Figure 2
Figure 2
Structure of radial basis neural network.
Figure 3
Figure 3
Structure of generalized regression neural network.
Figure 4
Figure 4
Structure of wavelet neural network.
Figure 5
Figure 5
Loss values of RBFNN and WNN on the dataset of this city in Northwest China.
Figure 6
Figure 6
Loss values of RBFNN and WNN on the Han dataset in central China cities.
Figure 7
Figure 7
Distribution of the ratio of the difference to the true value of the prediction data of different neural network models on the test dataset of the city in Northwest China.
Figure 8
Figure 8
Distribution of the proportion of the difference to the true value of the predicted data of different neural network models on the test dataset of this city in central China.
See this image and copyright information in PMC

References

    1. Mikowiec P. The impact of the mountain barrier on the spread of heavy metal pollution on the example of Gorce Mountains, Southern Poland. Environmental Monitoring and Assessment . 2022;194(9) - PMC - PubMed
    1. Čmiková N., Galovičová L., Miškeje M., Borotová P., Kluz M., Kačániová M. Determination of antioxidant, antimicrobial activity, heavy metals and elements content of seaweed extracts. Plants . 2022;11(11):p. 1493. doi: 10.3390/plants11111493. - DOI - PMC - PubMed
    1. Liu Z., Lu Y., Peng Y., Wang J., Ding S., Liu S. Estimation of soil heavy metal content using hyperspectral data. Remote Sensing . 2019;11(12):p. 1464.
    1. Pirsarandib Y., Hassanpouraghdam M. B., Rasouli F., Aazami M. A., Puglisi I., Baglieri A. Phytoremediation of soil contaminated with heavy metals via arbuscular mycorrhiza (funneliformis mosseae) inoculation ameliorates the growth responses and essential oil content in lavender (lavandula angustifolia L.) Agronomy . 2022;12(5):p. 1221. doi: 10.3390/agronomy12051221. - DOI
    1. Hou L., Wang Z., Gong G., et al. Hydrogen sulfide alleviates manganese stress in arabidopsis. International Journal of Molecular Sciences . 2022;23(9):p. 5046. doi: 10.3390/ijms23095046. - DOI - PMC - PubMed

LinkOut - more resources