Abstract
In view of the research about fuzzy time series models, the existing models are lack of objective data fuzzification and sensitivity. In this paper, firstly, a new method of defining fuzzy sets present is set up and six new fuzzy sets are given. Secondly, the rules of data fuzzification are defined. Finally, the model is used to forecast the enrollments of the University of Alabama. It is shown that the proposed model gets a higher forecasting accuracy than those which use traditional methods to forecast.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Song, Q., Chissom, B.S.: Fuzzy time series and its models [J]. Fuzzy Sets Syst. 54(1), 269–277 (1993)
Song, Q., Chissom, B.S.: Forecasting enrollments with fuzzy time series—Part I [J]. Fuzzy Sets Syst. 54(1), 1–10 (1993)
Song, Q., Chissom, B.S.: Forecasting enrollments with fuzzy time series—Part II [J]. Fuzzy Sets Syst. 62(l), 1–8 (1994)
Zadeh, L.: A. Fuzzy sets [J]. Inf. Control 8, 338–353 (1965)
Huarng, K., Yu, T.H.-K.: Ratio-based lengths of intervals to improve fuzzy time series forecasting [J]. IEEE Trans. Syst. Man Cybern. Part B: Cybern. 36(2), 328–340 (2006)
Li, S.-T., Cheng, Y.-C., Lin, S.-Y.: A FCM-based deterministic forecasting model for fuzzy time series [J]. Comput. Math. Appl. 56, 3052–3063 (2008)
Chen, S.M., Chung, N.Y.: Forecasting enrollments of students by using fuzzy time series and genetic algorithms [J]. Inf. Manage. Sci. 17(3), 1–17 (2006)
Optimization [J]. Expert Syst. Appl. 36(3), 6108–6117 (2009)
Chen, S.M., Hsu, C.C.: A new method to forecast enrollments using fuzzy time series [J]. Int. J. Appl. Sci. Eng. 3, 234–244 (2004)
Kuo, I.H., Horng, S.J., Kao, T.W., Lin, T.L., Lee, C.L., Pan, Y.: An improved method for forecasting enrollments based on fuzzy time series and particle swarm
Cheng, C.H., Chang, R.J., Yeh, C.A.: Entropy-based and trapezoidal Fuzzification based fuzzy time series approach for forecasting IT project cost [J]. Technol. Forecast. Soc. Change 73, 524–554 (2006)
Singh, P., Borah, B.: An efficient time series forecasting model based on fuzzy time series [J]. Eng. Appl. Artif. Intell. 26, 2443–2457 (2013)
Chen, S.M.: Forecasting enrollments based on fuzzy time series. Fuzzy Sets and Syst. 81, 311–319 (1996)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Chen, G., Yang, Lh., Yang, X. (2016). A Forecasting Approach of Fuzzy Time Series Model Based on a New Data Fuzzification. In: Cao, BY., Wang, PZ., Liu, ZL., Zhong, YB. (eds) International Conference on Oriental Thinking and Fuzzy Logic. Advances in Intelligent Systems and Computing, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-319-30874-6_29
Download citation
DOI: https://doi.org/10.1007/978-3-319-30874-6_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30873-9
Online ISBN: 978-3-319-30874-6
eBook Packages: EngineeringEngineering (R0)