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Convergence analysis of urban green traffic carbon emission based on grey prediction model

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  • Lede Niu
  • Mei Pan
  • Liran Xiong

Abstract

In order to overcome the big error of convergence test results of traditional methods, a convergence analysis method of urban green traffic carbon emission based on grey prediction model is proposed. The carbon emission data of three major areas of urban green traffic in recent years are collected, and the urban green traffic carbon emission is estimated according to the data collection results, and the spatial characteristics of the obtained urban green traffic carbon emission data are analysed data processing, including differentiation processing and clustering processing, based on the grey prediction model to build a convergence analysis model of urban green traffic carbon emissions, using the model to carry out convergence analysis of urban green traffic carbon emissions. The experimental results show that the standard error of the convergence test results of the proposed method is smaller than traditional methods, which verifies the effectiveness of the proposed method.

Suggested Citation

  • Lede Niu & Mei Pan & Liran Xiong, 2020. "Convergence analysis of urban green traffic carbon emission based on grey prediction model," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 42(5/6), pages 285-301.
    • Handle: RePEc:ids:ijgeni:v:42:y:2020:i:5/6:p:285-301
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    Cited by:

    1. Liping Zhu & Zhizhong Li & Xubiao Yang & Yili Zhang & Hui Li, 2022. "Forecast of Transportation CO 2 Emissions in Shanghai under Multiple Scenarios," Sustainability, MDPI, vol. 14(20), pages 1-18, October.

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