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Erschienen in: Neural Computing and Applications 15/2022

22.09.2021 | S.I. : Machine Learning based semantic representation and analytics for multimedia application

The correlation between green finance and carbon emissions based on improved neural network

verfasst von: Chenghao Sun

Erschienen in: Neural Computing and Applications | Ausgabe 15/2022

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Abstract

The development of green finance and the quantitative evaluation of its impact on the ecological environment provide empirical evidence for the construction of the carbon trading accounting system. Among them, carbon trading is an important part of green finance, and the accounting of businesses related to carbon emission rights has promoted the development of regional green finance. In order to explore the relationship between green finance and carbon emissions, this paper builds an analysis model of the relationship between green finance and carbon emissions based on big data and machine learning based on big data technology and machine learning technology. Moreover, this paper conducts simulation tests through the system and compares the output results with the actual situation after system simulation to verify the effectiveness of the model in this paper. From the experimental research results, it can be seen that the correlation analysis model of green finance and carbon emissions based on big data and machine learning constructed in this paper has a good performance in the correlation analysis of green finance and carbon emissions. Moreover, it is not difficult to see through the model of this paper that there is a clear correlation between green finance and carbon emissions.

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Metadaten
Titel
The correlation between green finance and carbon emissions based on improved neural network
verfasst von
Chenghao Sun
Publikationsdatum
22.09.2021
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 15/2022
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-021-06514-5

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