基于机器学习的绿色金融发展对生态保护的影响

Ting Zhang
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引用次数: 0

摘要

在绿色发展的今天,提高资源的利用率,引导产业的高质量发展,特别是将原本集中在高污染、高耗能行业的资金引导到绿色、高技术领域,实现经济与资源环境的协调发展,是各级金融部门的核心任务。提出了一种基于机器学习的绿色金融文本分类模型。该模型由四个模块组成:输入模块、数据分析模块、数据分类模块和分类模块。其中,数据分析模块和数据分类模块分别提取输入信息和绿色金融分类信息的数据信息,最后通过关注机制将两类信息融合,实现对金融数据中绿色金融数据的分类。在互联网金融文本数据集上进行了大量的实验,以证明所提出的绿色金融文本分类方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Impact of Green Finance Development on Ecological Protection Based on Machine Learning
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.
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