Analysis of seasonal time series using fuzzy approach

References

• Al-Smadi , A. 2009 . Automatic identification of ARMA systems . International journal of general systems , 38 : 29 – 41 .
   Web of Science ®Google Scholar
• Aznarte , J. , Benítez , J. and Castro , J. 2007 . Smooth transition autoregressive models and fuzzy rule-based systems: functional equivalence and consequences . Fuzzy sets and systems , 158 : 2734 – 2745 .
   Web of Science ®Google Scholar
• Bělohlávek , R. and Novák , V. 2002 . Learning rule base of the linguistic expert systems . Soft computing , 7 : 79 – 88 .
   Web of Science ®Google Scholar
• Brockwell , P. and Davis , R. 1998 . Time series: theory and methods , 2nd ed. , Springer Series in Statistics Heidelberg : Springer-Verlag .
   Google Scholar
• Bovas , A. and Ledolter , J. 2003 . Statistical methods for forecasting , New York : Wiley .
   Google Scholar
• Box , G. and Jenkins , G. 1970 . Time series analysis: forecasting and control , San Francisco : Holden-Day .
   Google Scholar
• Dvořák , A. 2003 . The software package LFLC 2000 – its specificity, recent and perspective applications . Computers in industry , 51 : 269 – 280 .
   Web of Science ®Google Scholar
• Habiballa , H. , Pavliska , V. and Dvořák , A. 2009 . Software system for time series prediction based on F-transform and linguistic rules . APLIMAT – Journal of applied mathematics , 1
   Google Scholar
• Hajičová , E. , Partee , B. and Sgall , P. 1998 . Topic-focus articulation, tripartite structures, and semantic content , Dordrecht : Kluwer .
   Google Scholar
• Hamilton , J.D. 1994 . Time series analysis , New Jersey : Princeton University Press .
   Google Scholar
• Huarng , K. 2001 . Heuristic models of fuzzy time series for forecasting . Fuzzy sets and systems , 123 : 369 – 386 .
   Web of Science ®Google Scholar
• Kasabov , N. and Song , Q. 2002 . DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction . IEEE transactions on fuzzy systems , 10 : 144 – 154 .
   Web of Science ®Google Scholar
• Leng , G. , McGinnity , T. and Prasad , G. 2005 . An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network . Fuzzy sets and systems , 150 : 211 – 243 .
   Web of Science ®Google Scholar
• Makridakis , S. and Hibon , K. 2000 . The M3-competition: results, conclusions and implications . International journal of forecasting , 16 : 451 – 476 .
   Web of Science ®Google Scholar
• Novák , V. 2005 . “ Perception-based logical deduction ” . In Computational intelligence, theory and applications (advances in soft computing) , Edited by: Reusch , B. 237 – 250 . Berlin, Germany : Springer .
   Google Scholar
• Novák , V. 2008 . A comprehensive theory of trichotomous evaluative linguistic expressions . Fuzzy sets and systems , 159 ( 22 ) : 2939 – 2969 .
   Web of Science ®Google Scholar
• Novák , V. , Perfilieva , I. and Močkoř , J. 1999 . Mathematical principles of fuzzy logic , Boston, MA : Kluwer Academic Publishers .
   Google Scholar
• Novák , V. and Perfilieva , I. 2004 . On the semantics of perception-based fuzzy logic deduction . International journal of intelligent systems , 19 : 1007 – 1031 .
   Web of Science ®Google Scholar
• Novák , V. 2008 . “ Analysis of periodical time series using soft computing methods ” . In Computational intelligence in decision and control , Edited by: Ruan , D. , Montero , J. , Lu , J. , Martínez , L. , D'hondt , P. and Kerre , E. 55 – 60 . Hackensack, NJ : World Scientific .
   Google Scholar
• Ord , K. , Hibon , K. and Makridakis , S. 2000 . The M3-competition . International journal of forecasting , 16 : 433 – 436 .
   Web of Science ®Google Scholar
• Perfilieva , I. 2006 . Fuzzy transforms: theory and applications . Fuzzy sets and systems , 157 : 993 – 1023 .
   Web of Science ®Google Scholar
• Perfilieva , I. and Valášek , R. 2005 . “ Fuzzy transforms in removing noise ” . In Computational intelligence, theory and applications (advances in soft computing) , Edited by: Reusch , B. 221 – 230 . Berlin, Germany : Springer .
   Google Scholar
• Perfilieva , I. Analysis and prediction of time series using fuzzy transform . Proceedings of IEEE world congress on computational intelligence . pp. 3875 – 3879 .
   Google Scholar
• Rong , H.J. 2006 . Sequential adaptive fuzzy inference system (SAFIS) for nonlinear system identification and prediction . Fuzzy sets and systems , 157 : 1260 – 1275 .
   Web of Science ®Google Scholar
• Sgall , P. 1986 . The meaning of the sentence in its semantic and pragmatic aspects , Boston, MA : Kluwer .
   Google Scholar
• Song , Q. and Chissom , B. 1993 . Fuzzy time series and its models . Fuzzy sets and systems , 54 : 269 – 277 .
   Web of Science ®Google Scholar
• Štěpnička, M., Lughofer, E. and Pavliska, V., 2006. Comparison of data-driven fuzzy modelling methods tested on NOx data. Abstracts of the 2nd FLLL/SCCH Master and PhD Seminar, 33–39
   Google Scholar
• Takagi , T. and Sugeno , M. 1985 . Fuzzy identification of systems and its applications to modeling and control . IEEE transactions on systems, man and cybernetics , 15 : 116 – 132 .
   Web of Science ®Google Scholar
• Tseng , F.M. 2001 . Fuzzy ARIMA model for forecasting the foreign exchange market . Fuzzy sets and systems , 118 : 9 – 19 .
   Web of Science ®Google Scholar
• Zadeh , L.A. 1973 . Outline of a new approach to the analysis of complex systems and decision processes . IEEE transactions on systems, man, and cybernetics , SMC-3 : 28 – 44 .
   Web of Science ®Google Scholar
• Zadeh , L.A. 1975 . The concept of a linguistic variable and its application to approximate reasoning I, II, III . Information sciences , : 8 – 9 . 199–257, 301–357, 43–80
   Google Scholar
• Zadeh , L.A. 2004 . Precisiated natural language . AI magazine , 25 : 74 – 91 .
   Web of Science ®Google Scholar