Abstract
In recent years, with the rapid economic growth in my country, environmental problems have become more severe, among which the problem of heavy metal pollution in soil is particularly prominent. Soil is the material basis for human survival. In order to ensure human health and achieve sustainable development, the control and treatment of soil heavy metal pollution is imminent. Based on the sparrow search algorithm, this paper establishes a soil quantitative detection model, and uses the algorithm’s population optimization performance to detect soil heavy metal content. And a detection model based on the improved algorithm was proposed, and the detection accuracy of the models under the two algorithms and the relative error of each heavy metal element were compared, and the effectiveness of the improved sparrow search algorithm in soil quantitative analysis was verified.
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Acknowledgements
This work was financed by the Technological Project of Heilongjiang Province “The open competition mechanism to select the best candidates” (No. 2022ZXJ05C01), Funding for the Opening Project of Key Laboratory of Agricultural Renewable Resource Utilization Technology (No. HLJHDNY2114) and Heilongjiang University of Science and Technology the introduction of high-level talent research start-up fund projects (No. 000009020315).
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Zhao, Q., Liu, K., Xiong, C., Yang, F. (2023). Establishment of Soil Quantitative Detection Model Based on Sparrow Search Algorithm. In: Li, A., Shi, Y., Xi, L. (eds) 6GN for Future Wireless Networks. 6GN 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 505. Springer, Cham. https://doi.org/10.1007/978-3-031-36014-5_3
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DOI: https://doi.org/10.1007/978-3-031-36014-5_3
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