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Nature Environmental Protection, 2023, 4(1); doi: 10.38007/NEP.2023.040108.

Coupling Dynamic Model of Natural Environment Protection and Environmental Pollution Based on Machine Learning

Author(s)

Herrera Victor

Corresponding Author:
Herrera Victor
Affiliation(s)

University of Sulimanyah Univ Sulaimani, Iraq

Abstract

As artificial intelligence develops, Machine Learning (ML) has gained more development opportunities. In the ecological field, the application of ML to Natural Environment Protection (hereinafter referred to as NEP) and Environmental Pollution (hereinafter referred to as EP) is currently a relatively hot field, which has been studied by many scholars. In order to explore the relationship between NEP and EP, this article constructed a Coupling Dynamic Model (hereinafter referred to as CDM) of NEP and EP based on ML through discussing ML and dynamic model. The model could reveal the stability of the positive balance of the natural ecosystem. Compared with the traditional way of building the dynamic model, the positive equilibrium stability values of the dynamic model in this method were controlled between 0.5 and 1.5. Its peak value changed less and its stability was better. This paper analyzed the relationship between natural environmental protection and EP by optimizing and innovating the dynamic model, thus providing more basis for the sustainable development of ecology.

Keywords

Coupling Dynamics Model, Machine Learning, Natural Environment Protection, Natural Environment Pollution

Cite This Paper

Herrera Victor. Coupling Dynamic Model of Natural Environment Protection and Environmental Pollution Based on Machine Learning. Nature Environmental Protection (2023), Vol. 4, Issue 1: 70-77. https://doi.org/10.38007/NEP.2023.040108.

References

[1] Korchenko Oleksandr. GIS and remote sensing as important tools for assessment of environmental pollution. International Multidisciplinary Scientific GeoConference: SGEM. (2019) 19(2.1): 297-304. https://doi.org/10.5593/sgem2019/2.1/S07.039

[2] Jing Sun. Urbanization, economic growth, and environmental pollution: Partial differential analysis based on the spatial Durbin model. Management of Environmental Quality: An International Journal. (2019) 30(2): 483-494. https://doi.org/10.1108/MEQ-05-2018-0101

[3] Baloch Zulfiqar Ali. Assessing energy efficiency in the Asia-Pacific region and the mediating role of environmental pollution: evidence from a super-efficiency model with a weighting preference scheme. Environmental Science and Pollution Research. (2021) 28(35): 48581-48594. https://doi.org/10.1007/s11356-021-13663-6

[4] Strassburg Bernardo BN. Global priority areas for ecosystem restoration. Nature. (2020) 586(7831): 724-729. https://doi.org/10.1038/s41586-020-2784-9

[5] Jacobides Michael G., Carmelo Cennamo, Annabelle Gawer. Towards a theory of ecosystems. Strategic management journal. (2018) 39.8: 2255-2276. https://doi.org/10.1002/smj.2904

[6] Gordin Igor. Environmental protection systems during periods of economic downturns. Ekonomika i matematicheskie metody. (2021) 57(2): 55-63. https://doi.org/10.31857/S042473880014913-3

[7] Zandalinas Sara I., Felix B. Fritschi, Ron Mittler. Global warming, climate change, and environmental pollution: recipe for a multifactorial stress combination disaster. Trends in Plant Science. (2021) 26(6): 588-599. https://doi.org/10.1016/j.tplants.2021.02.011

[8] Ng Archie. Fate of environmental pollutants. Water Environment Research. (2019) 91(10): 1294-1325. https://doi.org/10.1002/wer.1225

[9] Luka Yusufu, Bitrus Kwaji Highina, Abdu Zubairu. Bioremediation: A solution to environmental pollution-a review. Am J Eng Res. (2018) 7(2): 101-109.

[10] Tomislav Klarin. The concept of sustainable development: From its beginning to the contemporary issues. Zagreb International Review of Economics & Business. (2018) 21(1): 67-94. https://doi.org/10.2478/zireb-2018-0005

[11] Bali Swain, Ranjula, Fan Yang-Wallentin. Achieving sustainable development goals: predicaments and strategies. International Journal of Sustainable Development & World Ecology. (2020) 27(2): 96-106. https://doi.org/10.1080/13504509.2019.1692316

[12] Janiesch Christian, Patrick Zschech, Kai Heinrich. Machine learning and deep learning. Electronic Markets. (2021) 31(3): 685-695. https://doi.org/10.1007/s12525-021-00475-2

[13] Shiliang Sun. A survey of optimization methods from a machine learning perspective. IEEE transactions on cybernetics. (2019) 50(8): 3668-3681. https://doi.org/10.1109/TCYB.2019.2950779

[14] Ping Wang, Yan Li, Chandan K. Reddy. Machine learning for survival analysis: A survey. ACM Computing Surveys (CSUR). (2019) 51(6): 1-36. https://doi.org/10.1145/3214306

[15] Hopkins Emily. Machine learning tools, algorithms, and techniques. Journal of Self-Governance and Management Economics. (2022) 10(1): 43-55. https://doi.org/10.22381/jsme1012023