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

fYear

2012

fDate

6-8 Sept. 2012

Firstpage

146

Lastpage

151

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (IS), 2012 6th IEEE International Conference

Conference_Location

Sofia

Print_ISBN

978-1-4673-2276-8

Type

conf

DOI

10.1109/IS.2012.6335128

Filename

6335128