<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In the context of today’s green development, it is the core task of the financial sector at all levels to enhance the utilisation of resources and to guide the high-quality development of industries, especially to channel funds originally gathered in high-pollution and energy-intensive industries to sectors with green and high-technology, to achieve the harmonious development of the economy and the resources and environment. This paper proposes a green financial text classification model based on machine learning. The model consists of four modules: the input module, the data analysis module, the data category module, and the classification module. Among them, the data analysis module and the data category module extract the data information of the input information and the green financial category information respectively, and the two types of information are finally fused by the attention mechanism to achieve the classification of green financial data in financial data. Extensive experiments are conducted on financial text datasets collected from the Internet to demonstrate the superiority of the proposed green financial text classification method.</p>
</abstract>

In the context of today’s green development, it is the core task of the financial sector at all levels to enhance the utilisation of resources and to guide the high-quality development of industries, especially to channel funds originally gathered in high-pollution and energy-intensive industries to sectors with green and high-technology, to achieve the harmonious development of the economy and the resources and environment. This paper proposes a green financial text classification model based on machine learning. The model consists of four modules: the input module, the data analysis module, the data category module, and the classification module. Among them, the data analysis module and the data category module extract the data information of the input information and the green financial category information respectively, and the two types of information are finally fused by the attention mechanism to achieve the classification of green financial data in financial data. Extensive experiments are conducted on financial text datasets collected from the Internet to demonstrate the superiority of the proposed green financial text classification method.

The Impact of Green Finance Development on Ecological Protection Based on Machine Learning

Ecological Chemistry and Engineering S

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In the context of today’s green development, it is the core task of the financial sector at all levels to enhance the utilisation of resources and to guide the...

The Impact of Green Finance Development on Ecological Protection Based on Machine Learning

Publié en ligne: 10 avr. 2023

Pages: 103 - 110

DOI: https://doi.org/10.2478/eces-2023-0008

Mots clés
green finance, text classification, attention mechanisms, machine learning

© 2023 Ting Zhang, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The Impact of Green Finance Development on Ecological Protection Based on Machine Learning

Publié en ligne: 10 avr. 2023

Pages: 103 - 110

DOI: https://doi.org/10.2478/eces-2023-0008

Mots clésgreen finance, text classification, attention mechanisms, machine learning

© 2023 Ting Zhang, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
green finance, text classification, attention mechanisms, machine learning