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Academic Journal of Environmental Biology, 2022, 3(1); doi: 10.38007/AJEB.2022.030104.

Biological Monitoring Index of Fluorine Polluted Animal Husbandry Ecological Environment Based on Machine Learning Algorithm

Author(s)

Dazhi Xu, Yu Yuan and Xiaoyong Xiao

Corresponding Author:
Dazhi Xu
Affiliation(s)

College of Economics and Management, Hunan University of Arts and Science, Changde 415000, Hunan, China

Abstract

Fluorine widely exists in nature, and its element is one of the most oxidizing substances among all elements. It can even react with some inert gases to form corresponding fluorides. Due to this special chemical property, fluorine has a wide range of applications in many fields including medicine, chemical industry, aerospace and atomic energy. Therefore, the development of water defluorination technology is related to human health and happy life, as well as environmental health and water quality safety. The research purpose of this paper is the biological monitoring index of fluorine pollution animal husbandry ecological environment based on machine learning algorithm. Using machine learning algorithm and diversity index in the experiment, from the alarm value and grading standard of poultry manure load, the environmental impact of fluorine-contaminated livestock and poultry manure and other pollutants, and the biological monitoring of fluorine-contaminated livestock and poultry ecological environment three aspects of the indicators were analyzed experimentally.

Keywords

Machine Learning Algorithm, Fluorine Pollution, Animal Husbandry Ecological Environment, Biological Monitoring Indicators

Cite This Paper

Dazhi Xu, Yu Yuan and Xiaoyong Xiao. Biological Monitoring Index of Fluorine Polluted Animal Husbandry Ecological Environment Based on Machine Learning Algorithm. Academic Journal of Environmental Biology (2022), Vol. 3, Issue 1: 38-47. https://doi.org/10.38007/AJEB.2022.030104.

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