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Evaluation and Prediction of Ecological Environment based on Principal Component Analysis

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DOI: 10.23977/erej.2021.050411 | Downloads: 4 | Views: 169

Author(s)

Kaige Chen 1, Junhong Long 2, Huizhen Zheng 3

Affiliation(s)

1 School of Mechanical and Transportation, Taiyuan University of Technology Engineering, Taiyuan, Shanxi, 030002, China
2 School of computer science and Engineering, Jiangsu university of science and technology, Zhenjiang, Jiangsu, 212003, China
3 School of Public Administration, China University of Geosciences, Wuhan, Hubei, 430074, China

Corresponding Author

Huizhen Zheng

ABSTRACT

Based on HSB model, principal component analysis and linear fitting are used in this paper. First of all, 11 factors that may affect the ecological environment are collected and quantified. Secondly, the dimension of the influencing factors is reduced based on principal component analysis. Finally, the correlation coefficient between the main influencing factors and the ecological environment is obtained based on the linear model. The three factors that have the greatest impact on the environment of Saihanba are: climate resources factor, forest resources factor and water resources factor.

KEYWORDS

HSB model, Principal component analysis, Linear fitting

CITE THIS PAPER

Kaige Chen, Junhong Long, Huizhen Zheng, Evaluation and Prediction of Ecological Environment based on Principal Component Analysis. Environment, Resource and Ecology Journal (2021) 5: 55-59. DOI: http://dx.doi.org/10.23977/erej.2021.050411.

REFERENCES

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[2] Tian Jun, Liu Haiying, Cheng Shun, et al. Rumination on the climate and atmos-pheric contribution of Sehanba forest [J]. Hebei Forestry and Fruit Research, 2012
[3] Shen Songyu, Chen Weilin. Changes in vegetation cover in the source area of sand-storms--Beijing as an example, China Science and Technology Information, 2015
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[5] Qiu Shengrong, Zhang Ximing, Bai Ling et al. Study on the construction of nature reserve planning system in China, World Forestry Research, 2021.

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