Author
Abstract
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.
Suggested Citation
Yue Wang & S. E. Najafi, 2023.
"Application of Engineering Science Model Based on Fuzzy Sets in Enterprise Financial Evaluation Index,"
Advances in Mathematical Physics, Hindawi, vol. 2023, pages 1-10, April.
Handle:
RePEc:hin:jnlamp:5822589
DOI: 10.1155/2023/5822589
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlamp:5822589. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.