Title :
A TSK-based fuzzy system for telecommunications time-series forecasting
Author :
Mastorocostas, Paris A. ; Hilas, Constantinos S. ; Dova, Stergiani C. ; Varsamis, Dimitris N.
Author_Institution :
Dept. of Inf. & Commun., Technol. Educ. Inst. of Serres, Serres, Greece
Abstract :
A two-stage model-building process for generating a Takagi-Sugeno-Kang fuzzy forecasting system is proposed in this paper. Particularly, the Subtractive Clustering (SC) method is first employed to partition the input space and determine the number of fuzzy rules and the premise parameters. In the sequel, an Orthogonal Least Squares (OLS) estimator determines the input terms which should be included in the consequent part of each fuzzy rule and calculate their parameters. A comparative analysis with well-established forecasting models is conducted on real world tele-communications data, in order to investigate the forecasting capabilities of the proposed scheme.
Keywords :
forecasting theory; fuzzy set theory; fuzzy systems; least squares approximations; pattern clustering; telecommunication services; time series; OLS estimator; TSK-based fuzzy system; Takagi-Sugeno-Kang fuzzy forecasting system; comparative analysis; forecasting models; fuzzy rule; fuzzy rules; input space partition; orthogonal least squares estimator; subtractive clustering method; telecommunication data; telecommunication time-series forecasting; two-stage model-building process; Biological system modeling; Computational modeling; Forecasting; Input variables; Market research; Predictive models; Vectors; fuzzy modeling; orthogonal least squares; subtractive clustering; telecommunications time-series;
Conference_Titel :
Intelligent Systems (IS), 2012 6th IEEE International Conference
Conference_Location :
Sofia
Print_ISBN :
978-1-4673-2276-8
DOI :
10.1109/IS.2012.6335128
