基于PCA算法的低碳城市建设影响因素研究

在“双碳”目标背景下,城市作为落实低碳战略的重要主体,迎来了诸多挑战。为助力城市生态可持续发展,研究构建评价指标体系,量化数据并进行信效度分析,利用PCA算法对数据进行降维和特征提取,通过对主成分的解释和权重分析,确定关键影响因素。研究表明,影响低碳城市建设的关键因素分为环境、能源、建筑等八类,共11项指标。据此,探索低碳城市建设的优化路径与可行性策略,以促进“双碳”目标建设。

Research on Influencing Factors of Low-carbon City Construction Based on PCA Algorithm

Under the background of dual-carbon target, cities as the important subjects of low-carbon strategy implementation, have introduced many challenges. In order to help the sustainable development of urban ecology, the evaluation index system was constructed, the data was qualified and the reliability and validity were analyzed, PCA algorithm was used to degrade the data and extract the features, and the key influencing factors were determined by interpreting and analyzing the weights of the principal components. The result shows that the key factors affecting the construction of low-carbon cities are grouped into eight categories, including environment, energy and buildings, with a total of 11 indicators. Accordingly, the optimal path and feasible strategies for the construction of low-carbon cities are explored to promote the construction of dual-carbon goals.