Research on the national vulnerability of climate change based on principal component analysis

Chunhao Liu; Xuewu Qian; Dongming Song

doi:10.1117/12.2626414

21 December 2021 Research on the national vulnerability of climate change based on principal component analysis

Chunhao Liu, Xuewu Qian, Dongming Song

Proceedings Volume 12156, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021); 121561J (2021) https://doi.org/10.1117/12.2626414
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021), 2021, Sanya, China

Abstract

National fragility is an important indicator to measure the sustainable development of a country. This paper uses principal component analysis and multiple linear regression techniques to establish a model to assess the impact of climate change on national vulnerability. First of all, this paper analyzes the principal components of 12 indicators through SPSS software, and obtains the main indicators that affect China's vulnerability. Secondly, this article defines the national vulnerability index based on the mean and standard deviation of the main indicators, thus establishing a multivariate linear model based on principal component analysis, that is, the national vulnerability evaluation model. Finally, this article chooses Albania as the research object to predict the impact of climate change on the country’s vulnerability. The results show that climate change can directly and indirectly affect national vulnerability and increase its vulnerability.

Citation Download Citation

Chunhao Liu, Xuewu Qian, and Dongming Song "Research on the national vulnerability of climate change based on principal component analysis", Proc. SPIE 12156, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021), 121561J (21 December 2021); https://doi.org/10.1117/12.2626414

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