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Application of Engineering Science Model Based on Fuzzy Sets in Enterprise Financial Evaluation Index

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  • Yue Wang

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, 2023. "Application of Engineering Science Model Based on Fuzzy Sets in Enterprise Financial Evaluation Index," Advances in Mathematical Physics, John Wiley & Sons, vol. 2023(1).
    • Handle: RePEc:wly:jnlamp:v:2023:y:2023:i:1:n:5822589
    DOI: 10.1155/2023/5822589
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    References listed on IDEAS

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    1. Jinghua Li & Yiying Wang & Boxin Yang & Qinghua Zhou & Feihui Yuan, 2022. "Research on Fuzzy Decision‐Making Method of Task Allocation for Ship Multiagent Collaborative Design," Advances in Mathematical Physics, John Wiley & Sons, vol. 2022(1).
    2. Xincheng Zhu & Yan Zhang & Yunzhi Hou & Minda Jiang, 2022. "Evaluation and Analysis of Land Input‐Output Comprehensive Benefit Based on Fuzzy Mathematics and Analytic Hierarchy Process," Advances in Mathematical Physics, John Wiley & Sons, vol. 2022(1).
    3. Xincheng Zhu & Yan Zhang & Yunzhi Hou & Minda Jiang & S. E. Najafi, 2022. "Evaluation and Analysis of Land Input-Output Comprehensive Benefit Based on Fuzzy Mathematics and Analytic Hierarchy Process," Advances in Mathematical Physics, Hindawi, vol. 2022, pages 1-10, September.
    4. Jinghua Li & Yiying Wang & Boxin Yang & Qinghua Zhou & Feihui Yuan & S. E. Najafi, 2022. "Research on Fuzzy Decision-Making Method of Task Allocation for Ship Multiagent Collaborative Design," Advances in Mathematical Physics, Hindawi, vol. 2022, pages 1-20, July.
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