Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm

Traditional financial crisis prediction approaches have a tough time extracting the properties of financial data, resulting in financial crisis prediction with insufficient accuracy. As a result, based on the random forest algorithm, an intelligent financial crisis prediction approach for listed ent...

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Autores principales:	Mingxia Jiang, Xuexia Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology (General) T1-995 Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/685ed2ae5c824105924b3a5ec1bcd4bf
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spelling	oai:doaj.org-article:685ed2ae5c824105924b3a5ec1bcd4bf2021-11-08T02:35:59ZResearch on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm1939-012210.1155/2021/3807480https://doaj.org/article/685ed2ae5c824105924b3a5ec1bcd4bf2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3807480https://doaj.org/toc/1939-0122Traditional financial crisis prediction approaches have a tough time extracting the properties of financial data, resulting in financial crisis prediction with insufficient accuracy. As a result, based on the random forest algorithm, an intelligent financial crisis prediction approach for listed enterprises is proposed. The random forest method is used to mine the characteristics of financial data based on financial index data from publicly traded companies. This research develops a financial crisis prediction index system based on the findings of data feature mining. The CCR model is used to assess the efficiency of listed firms’ decision-making units with more input and output, and the efficiency index of each decision-making unit is calculated. The efficiency evaluation index of publicly traded companies is used to divide the severity of the financial crisis. The experimental results reveal that, when compared to standard prediction methods, this method’s forecast accuracy is commensurate with the actual state of businesses, and it can reduce the time it takes to predict financial crises.Mingxia JiangXuexia WangHindawi-WileyarticleTechnology (General)T1-995Science (General)Q1-390ENSecurity and Communication Networks, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995 Science (General) Q1-390
spellingShingle	Technology (General) T1-995 Science (General) Q1-390 Mingxia Jiang Xuexia Wang Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm
description	Traditional financial crisis prediction approaches have a tough time extracting the properties of financial data, resulting in financial crisis prediction with insufficient accuracy. As a result, based on the random forest algorithm, an intelligent financial crisis prediction approach for listed enterprises is proposed. The random forest method is used to mine the characteristics of financial data based on financial index data from publicly traded companies. This research develops a financial crisis prediction index system based on the findings of data feature mining. The CCR model is used to assess the efficiency of listed firms’ decision-making units with more input and output, and the efficiency index of each decision-making unit is calculated. The efficiency evaluation index of publicly traded companies is used to divide the severity of the financial crisis. The experimental results reveal that, when compared to standard prediction methods, this method’s forecast accuracy is commensurate with the actual state of businesses, and it can reduce the time it takes to predict financial crises.
format	article
author	Mingxia Jiang Xuexia Wang
author_facet	Mingxia Jiang Xuexia Wang
author_sort	Mingxia Jiang
title	Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm
title_short	Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm
title_full	Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm
title_fullStr	Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm
title_full_unstemmed	Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm
title_sort	research on intelligent prediction method of financial crisis of listed enterprises based on random forest algorithm
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/685ed2ae5c824105924b3a5ec1bcd4bf
work_keys_str_mv	AT mingxiajiang researchonintelligentpredictionmethodoffinancialcrisisoflistedenterprisesbasedonrandomforestalgorithm AT xuexiawang researchonintelligentpredictionmethodoffinancialcrisisoflistedenterprisesbasedonrandomforestalgorithm
_version_	1718443191275880448

Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm

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