Prediction method of urban traffic carbon emission reduction rate based on grey relational analysis

In order to more accurately predict the carbon emissions of urban transportation in my country, this paper proposes a method for predicting the reduction rate of urban transportation carbon emissions based on gray correlation analysis. Based on the principle of grey relational analysis, the influencing factors of China's carbon emissions were screened. On this basis, this paper constructed the prediction model of urban traffic carbon emission reduction rate, established the evaluation index data column, determined the reference index set, and standardized the data column Experiments show that the root mean square error of the method in this paper is less than that of the comparison method, and the average absolute percentage error is better than that of the LSSVR and ELM methods.