{"title":"基于机器学习的绿色金融发展对生态保护的影响","authors":"Ting Zhang","doi":"10.2478/eces-2023-0008","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":11395,"journal":{"name":"Ecological Chemistry and Engineering S","volume":"47 1","pages":"103 - 110"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Impact of Green Finance Development on Ecological Protection Based on Machine Learning\",\"authors\":\"Ting Zhang\",\"doi\":\"10.2478/eces-2023-0008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":11395,\"journal\":{\"name\":\"Ecological Chemistry and Engineering S\",\"volume\":\"47 1\",\"pages\":\"103 - 110\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Chemistry and Engineering S\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/eces-2023-0008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Chemistry and Engineering S","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/eces-2023-0008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.