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一种新型灰色 Verhulst 模型及其在 CO2 排放预测中的应用。

A novel Grey Verhulst model and its application in forecasting CO2 emissions.

机构信息

School of Economics & Management, Chongqing Normal University, Chongqing, 401131, China.

School of Science, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.

出版信息

Environ Sci Pollut Res Int. 2021 Jun;28(24):31370-31379. doi: 10.1007/s11356-020-12137-5. Epub 2021 Feb 19.

Abstract

Carbon dioxide emission is an important environmental issue, and it has also become an important reference factor for governments to formulate social and economic policies. The objective and accurate prediction of carbon dioxide emissions can provide reference and early warning for the implementation of the government's environmental strategy. The change of the original data of carbon dioxide emissions is S-type, but not saturated S-type. The grey Verhulst model is mainly used to describe the process with saturation state, which is suitable for modeling S-type data series. However, it is found that there are inherent errors and limitations in this model. In this paper, the grey action of the grey Verhulst model is improved, a new action Verhulst model is obtained, and its properties are studied. Finally, the new model is used to predict the carbon dioxide emissions of China and Russia, and ARIMA model is added for comparison. The results show that compared with the original Verhulst model, the simulation and prediction accuracy of the optimized Verhulst model are improved by more than 10%, and the ARIMA model underestimates the carbon dioxide emissions. From the result analysis, China and Russia need to formulate strong energy conservation and emission reduction policies, vigorously develop clean energy industry, and promote green production and lifestyle.

摘要

二氧化碳排放是一个重要的环境问题,也成为政府制定社会经济政策的重要参考因素。二氧化碳排放量的客观准确预测可以为政府环境战略的实施提供参考和预警。二氧化碳排放量原始数据的变化为 S 型,但不是饱和 S 型。灰色 Verhulst 模型主要用于描述具有饱和状态的过程,适用于 S 型数据序列的建模。然而,人们发现该模型存在内在误差和局限性。本文对灰色 Verhulst 模型的灰色作用进行了改进,得到了新的作用 Verhulst 模型,并对其性质进行了研究。最后,将新模型用于预测中国和俄罗斯的二氧化碳排放量,并与 ARIMA 模型进行比较。结果表明,与原始 Verhulst 模型相比,优化后的 Verhulst 模型的模拟和预测精度提高了 10%以上,而 ARIMA 模型低估了二氧化碳排放量。从结果分析来看,中国和俄罗斯需要制定强有力的节能减排政策,大力发展清洁能源产业,推动绿色生产和生活方式。

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