A Novel Forecasting Method Based on Markov‐Weighted Fuzzy Logical Relationships and F‐Transform

ABSTRACT This paper presents a novel time series forecasting method based on Markov‐weighted fuzzy logical relationships and the F‐transform. The proposed methodology comprises nine steps, ranging from data preprocessing to result evaluation, ensuring a systematic approach. It is validated using historical university enrolment data, and its performance is compared against seven benchmark methods. Experimental results highlight the method's superior predictive capabilities, demonstrating lower prediction errors, higher accuracy and an improved overall fit to the data.