Prediction of university fund revenue and expenditure based on fuzzy time series with a periodic factor

PLoS One. 2023 May 25;18(5):e0286325. doi: 10.1371/journal.pone.0286325. eCollection 2023.

Abstract

Financial management and decision-making of universities play an essential role in their development. Predicting fund revenue and expenditure of universities can provide a necessary basis for funds risk prevention. For the lack of solid data reference for financial management and funds risk prevention in colleges and universities, this paper presents a prediction model of University fund revenue and expenditure based on fuzzy time series with a periodic factor. Combined with the fuzzy time series, this prediction method introduces the periodic factor of university funds. The periodic factor is used to adjust the proportion of the predicted value of the fuzzy time series and the periodic observation value. A fund revenue prediction model and a fund expenditure prediction model are constructed, and an experiment is carried out with the actual financial data of a university in China. The experimental result shows the effectiveness of the proposed model, which can provide solid references for financial management and funds risk prevention in universities.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Financial Management*
  • Health Expenditures*
  • Humans
  • Time Factors
  • Universities

Grants and funding

This work was supported by the Education and Teaching Reform Special Fund for Central University (Grant No. 2021A49) and the Fundamental Research Funds for the Central Universities, China University of Geosciences (Grant No. 2021237).