Evolution simulation of spatial spillover effect of carbon emission efficiency based on improved PSO-PFCM clustering algorithm

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI:10.1117/12.3032126

Yufeng Chai, Yuehua Li, Bing Cai, Liang Han, Jiangbo Sha

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Abstract

By simulating and analyzing the spatial spillover effect between different regions, the spatial correlation of carbon emission efficiency can be studied. Understanding how carbon emission behaviors interact and transmit across regions will help to develop more comprehensive and accurate carbon emission management strategies. Therefore, a new evolutionary simulation method for spatial spillover effect of carbon emission efficiency is proposed in this study. The PSO-PFCM clustering algorithm was improved to detect the overflow of carbon emission efficiency. The main characteristics of the multidimensional spatial spillover effect of carbon emission efficiency were selected, the multidimensional spatial feature mapping model was constructed, and the level of spillover effect was judged to complete the analysis of the evolution of the spatial spillover effect of carbon emission efficiency. The experimental results show that the proposed method has shorter abnormal detection time of carbon emission data spill and higher evolutionary accuracy of spatial spillover effect of carbon emission efficiency.

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基于改进的 PSO-PFCM 聚类算法的碳排放效率空间溢出效应演化模拟

通过模拟分析不同区域间的空间溢出效应，可以研究碳排放效率的空间相关性。了解碳排放行为在不同区域间的相互作用和传递，有助于制定更全面、更准确的碳排放管理策略。因此，本研究提出了一种新的碳排放效率空间溢出效应的进化模拟方法。改进了 PSO-PFCM 聚类算法，以检测碳排放效率的溢出效应。选取碳排放效率多维空间溢出效应的主要特征，构建多维空间特征映射模型，判断溢出效应水平，完成碳排放效率空间溢出效应演化分析。实验结果表明，所提出的方法具有更短的碳排放数据溢出异常检测时间和更高的碳排放效率空间溢出效应演化精度。

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International Conference on Algorithms, Microchips and Network Applications

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