FUZZY TIME SERIES FORECASTING MODEL BASED ON VARIOUS TYPES OF SIMILARITY MEASURE APPROACH
Nik Muhammad Farhan Hakim Nik Badrul Alam, Nazirah Ramli · 2019
Fuzzy time series is well-known in forecasting the time series data. In this paper, we proposed an improved method for forecasting and used the proposed method to forecast the student enrollments in the University of Alabama and the unemployment rate in Malaysia. The performance of the forecasted results is tested using various similarity measures as proposed by the previous researchers. From these similarity measures, we identify the most exact similarity measure based on its average.