<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Among the many risks faced by colleges and universities, financial risk is one of the most important risks and has a large complexity. This paper evaluates the financial risk management level of colleges and universities using the fuzzy logic method based on the four dimensions of financial risk. The affiliation function is used to quantitatively describe fuzzy logic, and weighted summation is used to ensure the accuracy of fuzzy propositions. After selecting the evaluation indexes, the weights of the evaluation index system are determined, and a comprehensive evaluation system for financial risk management of colleges and universities is constructed. Taking Q colleges and universities in G city as the research object, the comprehensive evaluation coefficient of financial risk management of the subject colleges and universities is calculated, and the average value of the extensive risk coefficient of the subject colleges and universities in 2015–2017 is between 0 and 0.4, which belongs to the level of significant risk. The test university ranked second among 7 universities, but the comprehensive score index coefficient is 0.4898. However, there is still a large financial risk possibility. We need to formulate a corresponding risk management policy slightly.</p>
</abstract>

Among the many risks faced by colleges and universities, financial risk is one of the most important risks and has a large complexity. This paper evaluates the financial risk management level of colleges and universities using the fuzzy logic method based on the four dimensions of financial risk. The affiliation function is used to quantitatively describe fuzzy logic, and weighted summation is used to ensure the accuracy of fuzzy propositions. After selecting the evaluation indexes, the weights of the evaluation index system are determined, and a comprehensive evaluation system for financial risk management of colleges and universities is constructed. Taking Q colleges and universities in G city as the research object, the comprehensive evaluation coefficient of financial risk management of the subject colleges and universities is calculated, and the average value of the extensive risk coefficient of the subject colleges and universities in 2015–2017 is between 0 and 0.4, which belongs to the level of significant risk. The test university ranked second among 7 universities, but the comprehensive score index coefficient is 0.4898. However, there is still a large financial risk possibility. We need to formulate a corresponding risk management policy slightly.

Construction of Comprehensive Evaluation Model for Financial Risk Management in Colleges and Universities Based on Fuzzy Logic

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Among the many risks faced by colleges and universities, financial risk is one of the most important risks and has a large complexity. This paper evaluates the...

Construction of Comprehensive Evaluation Model for Financial Risk Management in Colleges and Universities Based on Fuzzy Logic

Publicado en línea: 03 jun 2024

Páginas: -

Recibido: 04 feb 2024

Aceptado: 15 abr 2024

DOI: https://doi.org/10.2478/amns-2024-1310

Palabras clave
Fuzzy logic, Affiliation function, Financial risk management, Evaluation modeling

© 2024 Linglin Zhao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Construction of Comprehensive Evaluation Model for Financial Risk Management in Colleges and Universities Based on Fuzzy Logic

Publicado en línea: 03 jun 2024

Páginas: -

Recibido: 04 feb 2024

Aceptado: 15 abr 2024

DOI: https://doi.org/10.2478/amns-2024-1310

Palabras claveFuzzy logic, Affiliation function, Financial risk management, Evaluation modeling

© 2024 Linglin Zhao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Fuzzy logic, Affiliation function, Financial risk management, Evaluation modeling