基于模糊集的工程科学模型在企业财务评价指标中的应用

IF 1 4区 物理与天体物理 Q3 PHYSICS, MATHEMATICAL Advances in Mathematical Physics Pub Date : 2023-04-01 DOI:10.1155/2023/5822589
Yue Wang
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引用次数: 0

摘要

随着社会的不断发展,企业之间的竞争日益激烈,有必要对企业的生产经营状况进行及时有效的分析。在信息技术发展的背景下,很多企业分析财务数据,企业财务分析指标是对企业经营的各种报表数据进行分析,能够有效反映企业的偿债、经营、盈利、发展能力。企业可以根据企业财务分析的指标,判断企业的经营状况,及时做出战略变革。然而,由于企业经营数据量大,不同类型数据之间的关系不同,在使用传统的企业财务分析指标进行分析时,对企业财务数据的分析不够准确。本文通过模糊集建立了工程科学模型,通过模糊分析提高了企业财务分析指标的数据分析能力。通过对基于模糊集的工程科学模型的企业财务分析指标与传统企业财务分析指标的比较,实验结果表明,基于模糊集的工程科学模型的企业财务分析指标与传统企业财务分析指标的财务信息分析平均准确率分别为84%和74%。因此,将基于模糊集的工程科学模型应用到企业财务分析指标中,可以有效地提高财务信息分析的准确性。
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Application of Engineering Science Model Based on Fuzzy Sets in Enterprise Financial Evaluation Index
With the continuous development of society and the increasingly fierce competition among enterprises, it is necessary to analyze the production and operation conditions of enterprises in a timely and effective manner. In the context of the development of information technology, many companies analyze financial data, and corporate financial analysis indicators are the analysis of various report data of the company’s operations, which can effectively reflect the company’s debt repayment, operation, profit, and development capabilities. Enterprises can judge the operation status of the enterprise and make strategic changes in time according to the indicators of enterprise financial analysis. However, due to the large amount of operational data of enterprises and different relationships among different types of data, the analysis of enterprise financial data is not accurate enough when using traditional enterprise financial analysis indicators for analysis. This paper established an engineering scientific model through fuzzy sets and improved the data analysis ability of enterprise financial analysis indicators in enterprises by means of fuzzy analysis. By comparing the enterprise financial analysis indicators of the engineering science model based on fuzzy sets and the traditional enterprise financial analysis indicators, the experimental results showed that the average financial information analysis accuracy of the enterprise financial analysis index based on the engineering science model based on fuzzy sets and the traditional enterprise financial analysis index are 84% and 74%, respectively. Therefore, applying the engineering science model based on fuzzy sets to the corporate financial analysis indicators can effectively improve the accuracy of financial information analysis.
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来源期刊
Advances in Mathematical Physics
Advances in Mathematical Physics 数学-应用数学
CiteScore
2.40
自引率
8.30%
发文量
151
审稿时长
>12 weeks
期刊介绍: Advances in Mathematical Physics publishes papers that seek to understand mathematical basis of physical phenomena, and solve problems in physics via mathematical approaches. The journal welcomes submissions from mathematical physicists, theoretical physicists, and mathematicians alike. As well as original research, Advances in Mathematical Physics also publishes focused review articles that examine the state of the art, identify emerging trends, and suggest future directions for developing fields.
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