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Pollutant transmission model in marine food web based on complex network
Yunlong PENG, Han LI, Tian SANG, Hongming CHENG
Journal of Computer Applications    0, (): 143-147.   DOI: 10.11772/j.issn.1001-9081.2024040476
Abstract24)   HTML1)    PDF (2327KB)(6)       Save

In response to the serious damage to the global marine ecosystem caused by the discharge of nuclear wastewater into the sea. In this paper, a marine biological pollution transmission model based on complex network was proposed for estimating and simulating the transmission of pollutants. Firstly, a complex network was constructed on the basis of the predation relationships among some biological communities in northern waters of Jiangsu offshore area, Kongsi Gorge sea area, and northern area of Barents Sea. Secondly, the Euler convection diffusion equation was used to simulate the diffusion of pollutants in the assumed sea area, and then the pollutant exchange relationship between the marine environment and organisms was considered, and combined with the pollution transmission based on predation relationship, the final transmission model was constructed. Thirdly, outlier analysis was conducted on the basis of corresponding relationship between the comprehensive importance of nodes and the nutritional levels of biological communities, and potential anomalies in model fitting were analyzed. Finally, the concentration of pollutants of biological nodes in the network changing over time was simulated, and the fitting verification was carried out based on the relationship between the nutrient level of biological communities and pollutant concentration corresponding to each real network. Experimental results show that the fitting effect of the proposed model meets the biological accumulation and amplification phenomena of pollutants on the food web, and is mutually verified with the isotope detection results of some biological nodes in Barents Sea. All of the fitting data and real data verify the effectiveness of the proposed model in terms of mean square error, correlation coefficient, mean absolute error, R-squared, and statistical test.

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