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Fuzzy Time Series Forecasting Based On K-Means Clustering

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DOI: 10.4236/ojapps.2012.24B024    2,556 Downloads   4,634 Views   Citations

ABSTRACT

Many forecasting models based on the concepts of Fuzzy time series have been proposed in the past decades. These models have been widely applied to various problem domains, especially in dealing with forecasting problems in which historical data are linguistic values. In this paper, we present a new fuzzy time series forecasting model, which uses the historical data as the universe of discourse and uses the K-means clustering algorithm to cluster the universe of discourse, then adjust the clusters into intervals. The proposed method is applied for forecasting University enrollment of Alabama. It is shown that the proposed model achieves a significant improvement in forecasting accuracy as compared to other fuzzy time series forecasting models.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Zhang, Z. and Zhu, Q. (2012) Fuzzy Time Series Forecasting Based On K-Means Clustering. Open Journal of Applied Sciences, 2, 100-103. doi: 10.4236/ojapps.2012.24B024.

References

[1] Q. Song, B.S. Chissom, “Forecasting enrollments with fuzzy time series—Part I”, Fuzzy Sets and Systems, 54 (1993b) 1-10.
[2] Q. Song, B.S. Chissom, “Forecasting enrollments with fuzzy time series—Part II”, Fuzzy Sets and Systems, 62 (1994) 1-8.
[3] S. M. Chen, “Forecasting enrollments based on fuzzy time series”, Fuzzy Sets and Systems, 81 (1996) 311-319.
[4] J. R. H Wang, S. M. Chen, C. H. Lee, “:Handing forecasting problems using fuzzy time series”, Fuzzy Sets and Systems, 100 (1998) 217-228.
[5] K. Huarng, “Heuristic models of fuzzy time series for forecasting”, Fuzzy Sets and Systems, 123 (2001) 369-386.
[6] T. A. Jilani, S. M. A. Burney, C. Ardil, “ Fuzzy metric approach for fuzzy time series forecasting based on frequency density based partitioning”, In: Proceedings of World Academy of Science, Engineering and Technology 23 (2009) 1307-6884.

  
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