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

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

By: Ting Zhang  
Open Access
|Apr 2023

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.

DOI: https://doi.org/10.2478/eces-2023-0008 | Journal eISSN: 2084-4549 | Journal ISSN: 1898-6196
Language: English
Page range: 103 - 110
Published on: Apr 10, 2023
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Ting Zhang, published by Society of Ecological Chemistry and Engineering
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.