@article{(Open Science Index):https://publications.waset.org/pdf/11571,
	  title     = {Fuzzy Metric Approach for Fuzzy Time Series Forecasting based on Frequency Density Based Partitioning},
	  author    = {Tahseen Ahmed Jilani and  Syed Muhammad Aqil Burney and  C. Ardil},
	  country	= {},
	  institution	= {},
	  abstract     = {In the last 15 years, a number of methods have been proposed for forecasting based on fuzzy time series. Most of the fuzzy time series methods are presented for forecasting of enrollments at the University of Alabama. However, the forecasting accuracy rates of the existing methods are not good enough. In this paper, we compared our proposed new method of fuzzy time series forecasting with existing methods. Our method is based on frequency density based partitioning of the historical enrollment data. The proposed method belongs to the kth order and time-variant methods. The proposed method can get the best forecasting accuracy rate for forecasting enrollments than the existing methods.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {4},
	  number    = {7},
	  year      = {2010},
	  pages     = {1194 - 1199},
	  ee        = {https://publications.waset.org/pdf/11571},
	  url   	= {https://publications.waset.org/vol/43},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 43, 2010},
	}