Title : 
A new method to predict enrollments based on fuzzy time series
         
        
        
            Author_Institution : 
Inst. of Electr. Eng., Henan Univ. of Technol., Zhengzhou, China
         
        
        
        
        
            Abstract : 
In this paper, we propose a new method for enrollments prediction, based on fuzzy time series. The new method constructs high-order fuzzy logical relationships with high-order heuristic function based on the historical data and uses nature-ratio techniques to partition the length of each interval in the universe of discourse for enrollments forecasting to increase the prediction accuracy rate. The proposed method gets a higher forecasting accuracy rate than some existing methods.
         
        
            Keywords : 
forecasting theory; fuzzy set theory; time series; enrollments forecasting; enrollments prediction; fuzzy time series; high-order fuzzy logical relationships; high-order heuristic function; Accuracy; Artificial neural networks; Computational modeling; Forecasting; Fuzzy sets; Predictive models; Time series analysis; enrollments forecasting; high-order fuzzy logical relationships; high-order heuristic function; nature-ratio partition;
         
        
        
        
            Conference_Titel : 
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
         
        
            Conference_Location : 
Jinan
         
        
            Print_ISBN : 
978-1-4244-6712-9
         
        
        
            DOI : 
10.1109/WCICA.2010.5553945