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<p>Exploring the coupled and coordinated relationship between green finance and economic growth is to achieve the high-quality dual development of green and economy. This paper studies the rough set and information entropy attribute approximate calculation based on MapReduce parallel computing framework under big data technology. The basic principles of rough set and information entropy are described, and the MapReduce algorithm is used to calculate information entropy, mutual information, and attribute kernel, which shows that MapReduce calculation is always on the key-value pairs. For the correlation analysis of green finance and economic growth, the coupled coordination model of green finance and economic growth is constructed using the MapReduce algorithm, and the coupled coordination analysis of green finance and economic growth is carried out for this model. From the comprehensive evaluation index, the comprehensive evaluation index of green finance and economic growth increased by 6308.44% and 2242.21%, respectively. The coupling degree of green finance and economic growth increased by 164.66% and 835.84% from the coupling degree and coordination degree, respectively. Thus, the coupling relationship between green finance and economic growth based on big data is relatively low, but the coordination degree is high, indicating that the two influence each other and interact.</p>
</abstract>

Exploring the coupled and coordinated relationship between green finance and economic growth is to achieve the high-quality dual development of green and economy. This paper studies the rough set and information entropy attribute approximate calculation based on MapReduce parallel computing framework under big data technology. The basic principles of rough set and information entropy are described, and the MapReduce algorithm is used to calculate information entropy, mutual information, and attribute kernel, which shows that MapReduce calculation is always on the key-value pairs. For the correlation analysis of green finance and economic growth, the coupled coordination model of green finance and economic growth is constructed using the MapReduce algorithm, and the coupled coordination analysis of green finance and economic growth is carried out for this model. From the comprehensive evaluation index, the comprehensive evaluation index of green finance and economic growth increased by 6308.44% and 2242.21%, respectively. The coupling degree of green finance and economic growth increased by 164.66% and 835.84% from the coupling degree and coordination degree, respectively. Thus, the coupling relationship between green finance and economic growth based on big data is relatively low, but the coordination degree is high, indicating that the two influence each other and interact.

Coupled coordination analysis of green finance on economic growth based on big data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Exploring the coupled and coordinated relationship between green finance and economic growth is to achieve the high-quality dual development of green and...

Coupled coordination analysis of green finance on economic growth based on big data

Publié en ligne: 16 août 2023

Pages: -

Reçu: 12 sept. 2022

Accepté: 24 févr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00194

Mots clés
MapReduce algorithm, Rough set, Information entropy, Green finance, Parallel computing

© 2023 Su Guo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Coupled coordination analysis of green finance on economic growth based on big data

Publié en ligne: 16 août 2023

Pages: -

Reçu: 12 sept. 2022

Accepté: 24 févr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00194

Mots clésMapReduce algorithm, Rough set, Information entropy, Green finance, Parallel computing

© 2023 Su Guo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
MapReduce algorithm, Rough set, Information entropy, Green finance, Parallel computing