Exploring the impact mechanism of low-carbon multivariate coupling system in Chinese typical cities based on machine learning.

At the same time, in terms of the coupling and coordination between low-carbon levels and economic development, the temporal trend shows an increasing trend year by year, and the relationship between the two is in line with the “inverted U-shaped” characteristics.

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Meanwhile, the influence mechanism of the multi-coupled system is investigated using the coupling coordination degree model and random forest algorithm.The results show that there are 8 cities with a significant increasing trend of low-carbon level, 19 cities with no significant monotonic change trend, and 3 cities with a decreasing trend of low-carbon level.

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