Analysis of Climate Expectation Mitigation Based on Green GDP

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Year:
2023
Type of Publication:
Article
Keywords:
Green GDP, Portfolio Assignment Method, Climate Mitigation Expectations, BP Neural Network
Authors:
Ruizhen Xv; Yulian Tang; Zhendong Jiang; Dongyan Wang; Wenying He
Journal:
IJISM
Volume:
11
Number:
3
Pages:
56-66
Month:
May
ISSN:
2347-9051
Abstract:
In the context of increasingly severe resource and environmental problems, the inadequacy of GDP as a core economic indicator that does not reflect resource and environmental factors is increasingly highlighted. In this regard, this paper analyzes the changes of other indicators such as climate globally under the influence of GGDP and the future evolution trend by collecting data on the impact of green GDP and other climate indicators in different countries worldwide and building a relevant machine learning model. Firstly, the green GDP is defined and the direct and indirect factors affecting the environment are selected as indicators, while the weight correction coefficients are introduced, and the green GDP model is revised using the entropy weight method combined with the variance coefficient method of combined weighting, resulting in the improved green GDP model. Subsequently, the factor system was constructed and the data were merged to establish a global climate mitigation expected impact model based on BP neural network, and the model generalization ability was better. On the basis of this, on behalf of the U.S. as an example, the green GDP data of the U.S. were substituted, and it was finally concluded that the change trend of the U.S. data was the same as that of the other four continents, and the model had good generalizability, and the accounting of green GDP could effectively mitigate the climate effect.

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