An Improved Time Series Model

Fuzzy time series have demonstrated considerable prowess in addressing nebulous and indeterminate data. In order to enhance the predictive accuracy of the model, this research integrates fixed-point theory with time series analysis, introducing the concepts of fractional functions, inverse fractional functions, and predictive functions, while also demonstrating the convergence of these predictive functions. Building on this foundation, the paper further refines the theory of fuzzy time series by establishing a fixed-point-based fuzzy time series model, which has been applied to forecast the enrollment numbers at the University of Alabama and the sales volume of new energy vehicles in China. The prediction results showed the models high accuracy, robust theoretical foundations, and broad applicability.