Download presentation
Presentation is loading. Please wait.
Published byGiselle Daisley Modified over 10 years ago
1
Forecasting Enrollment Model Based on First-Order Fuzzy Time Series By Melike Şah ( * ) Konstantin Y. Degtiarev İnternational Conference on Computational İntelligence (İCCİ) 17-19 December 2004, İstanbul, Turkey
2
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series2 Overview Introduction Fuzzy Time Series Forecasting Enrollments with a new Time- Invariant Fuzzy Time Series method Forecasting Results and Discussion Conclusion References
3
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series3 Introduction Forecasting: weather, staff scheduling, finance Well-known forecasting methods cannot solve problems, when data are available in linguistic form A new Time-Invariant Fuzzy Time Series method to forecast University of Alabama enrollment The effect of different number of fuzzy sets Comparison with Song & Chissom and Chen’s time invariant-methods (see Reference section, slide 15)
4
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series4 Fuzzy Time Series First-order fuzzy time series Fuzzy Logical Relationship ; Forecasting is an operator
5
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series5 A New method of Time-Invariant Fuzzy Time Series Variations of University of Alabama enrollment At fuzzification stage different number of fuzzy sets [5-9] used. Intervals and linguistic variables of 6 fuzzy sets as, …. (big decrease), (decrease), (no change), (increase), (big increase), (too big increase)
6
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series6 Fuzzified variations of University of Alabama enrollment
7
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series7 A New method of Time-Invariant Fuzzy Time Series (Cont.) First-order fuzzy logical relationships: Years Fuzzified Variations 1972 A4 1973 A4 1974 A5 1975 A5 1976 A3 …
8
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series8 A New method of Time-Invariant Fuzzy Time Series (Cont.) Group fuzzy logical relationships: - union of relationships in each group
9
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series9 A New method of Time-Invariant Fuzzy Time Series (Cont.) Forecasting: Deffuzification: If MF all 0 forecasted variation is 0 If MF has one Max midpoint of that interval If MF has two or more consecutive Maxs Midpoint of corresponding conjunct intervals Otherwise Centroid of the output
10
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series10 Forecasted Outputs and Actual Enrollments from 1973-1993
11
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series11 Results and Discussion The proposed method is implemented in MATLAB
12
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series12 Results and Discussion (Cont.)
13
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series13 Results and Discussion (Cont.) Different number of fuzzy sets:
14
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series14 Conclusion Sorely available historical data used for forecasting Significantly improves accuracy For all examined cases (different number of fuzzy sets) forecasting error below 3%
15
Melike Şah, Konstantin Y. Degtiarev Forecasting Enrollment Model Based on First-Order Fuzzy Time series15 References Q. Song and B.S. Chissom, “Fuzzy time series and its models”, Fuzzy Sets and Systems, vol. 54, pp. 269-277, 1993. Q. Song and B.S. Chissom, “Forecasting enrollments with fuzzy time series – part 1”, Fuzzy Sets and Systems, vol. 54, pp. 1-9, 1993. Q. Song and B.S. Chissom, “Forecasting enrollments with fuzzy time series – part 2”, Fuzzy Sets and Systems, vol. 62, pp. 1-8, 1994. S.-M. Chen, “Forecasting Enrollments Based on Fuzzy Time Series”, Fuzzy Sets and Systems, vol. 81, pp. 311-319, 1996. S.-M. Chen, “Temperature Prediction using Fuzzy Time Series”, IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, vol. 30, pp. 263-275, 2000. K.Huarng, “Heuristic Models of Fuzzy Time Series for Forecasting”, Fuzzy Sets and Systems, vol. 123, pp. 369-386, 2001.
16
Thank you for attention! Do you have any Questions?
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.