Academic Journal of Environment & Earth Science, 2023, 5(7); doi: 10.25236/AJEE.2023.050703.
Wenzhuo Chen1, Ziqi Gao2, Hao Wang3, Zhongpeng Liu4, Haojun Hu5
1School of Shipping and Naval Architecture, Chongqing Jiaotong University, Chongqing, 402247, China
2College of Civil Engineering, Chongqing Jiaotong University, Chongqing, 402247, China
3Institute of Finance and Economics, Qinghai University, Xining, Qinghai, 810016, China
4Clinical Medical Technology College, Sichuan Health Rehabilitation Vocational College, Zigong, Sichuan, 643000, China
5Sichuan Vocational College of Judicial Police, Deyang, Sichuan, 618000, China
In this paper, the light pollution problem is studied. Firstly, the principal component analysis method is used to delete and merge the existing data, so as to get the final judgment index. Secondly, the entropy weight method and TOPSIS evaluation method were combined to obtain the light pollution risk index (LDI) with comprehensive scores, and the K-Means clustering method was adopted to classify figure the light pollution risk levels according to LDI. Finally, indicators were collected and ranked for four regions: protected area, rural community, suburban community and urban community, so as to determine their risk levels. The study found that the levels of light pollution risk in protected areas, rural communities, suburban communities and urban communities gradually increased.
Entropy weighting method; TOPSIS; K-means
Wenzhuo Chen, Ziqi Gao, Hao Wang, Zhongpeng Liu, Haojun Hu. Research on light pollution problem based on K-means regression. Academic Journal of Environment & Earth Science (2023) Vol. 5 Issue 7: 21-27. https://doi.org/10.25236/AJEE.2023.050703.
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