Academic Journal of Computing & Information Science, 2023, 6(7); doi: 10.25236/AJCIS.2023.060708.
Guanqiao Wang, Heng Zhou, Bohang Lin
School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China
Carbon emissions are silent but deadly poison that threaten the environment human live. To accurately assess each country's level of attitudes and commitment in reducing carbon emissions, the article establishes an evaluation model of carbon emissions reduction performance. First of all, TOPSIS based on the entropy weight method (EWM) is adopted to score 198 countries. Then, K-Means clustering algorithm is used to classify the countries into five distinct categories: Top, Good, Middle, Underachievers, and Poor. The number of countries in each category is 5, 66, 51, 36, and 40 respectively. To verify the rationality of classification, carbon emissions data from 1970 to 2021 around the world is utilized to conduct Spearman correlation analysis.
Carbon emissions reduction, TOPSIS, K-Means clustering algorithm, Correlation analysis
Guanqiao Wang, Heng Zhou, Bohang Lin. Evaluation of Carbon Emissions Redcution Performance Based on TOPSIS and K-Means Clustering Algorithm. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 7: 51-58. https://doi.org/10.25236/AJCIS.2023.060708.
[1] Udara Willhelm Abeydeera L H, Wadu Mesthrige J, Samarasinghalage T I. Global research on carbon emissions: A scientometric review [J]. Sustainability, 2019, 11(14): 3972.
[2] He Y, Xing Y, Zeng X, et al. Factors influencing carbon emissions from China's electricity industry: Analysis using the combination of LMDI and K-means clustering [J]. Environmental Impact Assessment Review, 2022, 93: 106724.
[3] Mohsin M, Rasheed A K, Sun H, et al. Developing low carbon economies: an aggregated composite index based on carbon emissions[J]. Sustainable Energy Technologies and Assessments, 2019, 35: 365-374.
[4] Feng H, Wang R, Zhang H. Research on Carbon Emission Characteristics of Rural Buildings Based on LMDI-LEAP Model [J]. Energies, 2022, 15(24): 9269.
[5] Zeng Ye, Jia Heping, Yang Jing, Wang Wei, Zhong Hua, Han Jinshan, Liu Dunnan. Comprehensive Contribution Degree Evaluation Method of Virtual Power Plants Based on FAHP-EWM-TOPSIS Method [J/OL]. Modern Electric Power: 1-8[2023-03-07]. DOI: 10. 19725/j. cnki. 1007-2322. 2022. 0188.
[6] Yang Jin, Wang Zhongwei, Pang Yan. Performance evaluation of camellia industry development based on entropy TOPSIS method [J]. Journal of Central South University of Forestry and Technology, 2021, 41(12): 168-177. DOI: 10. 14067/j. cnki. 1673- 923x. 2021. 12. 019.
[7] An R, Zhu G. Clustering of economic efficiency of urban energy carbon emissions based on decoupling theory [J]. Energy Reports, 2022, 8: 9569-9575.
[8] Sammouda Rachid, El Zaart Ali. An Optimized Approach for Prostate Image Segmentation Using K-Means Clustering Algorithm with Elbow Method [J]. Computational Intelligence and Neuroscience, 2021, 2021.
[9] Mishra P, Pandey C M, Singh U, et al. Descriptive statistics and normality tests for statistical data[J]. Annals of cardiac anaesthesia, 2019, 22(1): 67.
[10] Lan Wenbao, Che Chang, Tao Chengyun. Selection of monogenic components based on Spearman rank correlation with application to SAR target recognition [J]. Chinese Journal of Radio Science, 2020, 35(03): 414- 421. DOI: 10. 13443/j. cjors. 2019063001.
[11] Wang Z, Lv J, Tan Y, et al. Temporospatial variations and Spearman correlation analysis of ozone concentrations to nitrogen dioxide, sulfur dioxide, particulate matters and carbon monoxide in ambient air, China[J]. Atmospheric Pollution Research, 2019, 10(4): 1203-1210.