Fuzzy transforms method in prediction data analysis

Fuzzy Sets and Systems

Volumn 180, Issue 1, 2011, Pages 146-163

  Di Martino, Ferdinando ^a   Loia, Vincenzo ^b   Sessa, Salvatore ^a  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

^b UNIVERSITY OF SALERNO   (Italy)

Author keywords

Forecasting time series; Fuzzy partition; Fuzzy rule set; Fuzzy transform

Indexed keywords

CHAOTIC TIME SERIES; CLIMATIC INDEX; FORECASTING PROBLEMS; FORECASTING TIME SERIES; FUZZY PARTITION; FUZZY RULE SET; FUZZY TRANSFORMS; LOCAL LINEAR; PREDICTION METHODS; WAVELET NEURAL NETWORKS;

DATA REDUCTION; FUZZY SYSTEMS; NEURAL NETWORKS; TIME SERIES;

FORECASTING;

EID: 79960619498     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fss.2010.11.009     Document Type: Article

References (65)

1. B. Abraham, and J. Ledolter Statistical Methods for Forecasting 1983 John Wiley & Sons New York
2. J.M. Alonso, L. Magdalena, S. Guillaume, KBCT: a knowledge extraction and representation tool for fuzzy logic based systems, in: Proceedings of the FUZZ-IEEE, vol. 2, Budapest, 2004, pp. 989-994. (Pubitemid 40028033)
3. P.P. Angelov, and R.A. Buswell Automatic generation of fuzzy rule-based models from data by genetic algorithms Information Sciences 150 1-2 2003 17 31
4. J.S. Armstrong (Ed.), Principles of Forecasting: A Handbook for Researchers and Practitioners, University of Pennsylvania, Wharton School, Philadelphia, 2001.
5. G.E.P. Box, G.M. Jenkins, and G.C. Reinsel Time Series Analysis: Forecasting and Control third ed. 1994 Prentice Hall Englewood Cliffs
6. J. Casillas, O. Cordón, and F. Herrera COR: a methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules IEEE Transactions on Systems, Man, and Cybernetics - Part B 32 4 2002 526 537
7. J. Casillas, O. Cordón, M.J. del Jesus, and F. Herrera Genetic tuning of fuzzy rule deep structures preserving interpretability and its interaction with fuzzy rule set reduction IEEE Transactions on Fuzzy Systems 13 1 2005 13 29 (Pubitemid 40319306)
8. J. Casillas, A. Orriols-Puig, E. Bernado-Mansilla, Toward evolving consistent, complete and compact fuzzy rule-sets for classification problems, in: Proceedings of the 3rd International Workshop on Genetic and Evolving Systems, No. 4-7, 2008, pp. 89-94.
9. P.C. Chang, and C.H. Liu A TSK type fuzzy rule based system for stock price prediction Expert Systems with Applications 34 2008 135 144
10. T. Chen, and M.J. Wang Forecasting methods using fuzzy concepts Fuzzy Sets and Systems 105 1999 339 352 (Pubitemid 129524493)
11. Y. Chen, B. Yang, J. Dong, and A. Abraham Time-series forecasting using flexible neural tree model Information Sciences 174 2005 219 235 (Pubitemid 40893971)
12. S.M. Chen, S.H. Lee, and C.H. Lee A new method for generating fuzzy rules from numerical data for handling classification problems Applied Artificial Intelligence 15 7 2001 645 664
13. Y. Chen, B. Yang, and J. Dong Time-series prediction using a local linear wavelet neural network Neurocomputing 69 2006 449 456
14. Y. Chen, J. Dong, B. Yang, Y. Zhang, A local linear wavelet neural network, in: Proceedings of the 5th World Congress on Intelligent Control and Automation, vol. 3, 2004, pp. 1954-1957.
15. R. Chen, and R.S. Tsay Functional-coefficient autoregressive models Journal of the American Statistical Association 88 1993 298 308
16. M.E. Cintra, H. de Arunda Camargo, M.C. Monard, Fuzzy feature subset selection using the Wang-Mendel method, in: Proceedings of the 8th International Conference on Hybrid Intelligent Systems, Barcelona, 2008, pp. 590-595.
17. M.P. Clements, P.H. Franses, and N.R. Swanson Forecasting economic and financial time-series with non-linear models International Journal of Forecasting 20 2 2004 169 183 (Pubitemid 38461923)
18. M.P. Clements, C. Milas, and D. van Dijk Forecasting returns and risk in financial markets using linear and nonlinear models International Journal of Forecasting 25 2 2009 215 217
19. D. Danilov, A.A. Zhigljavsky (Eds.), Principal Components of Time Series: The Caterpillar Method, University of St. Petersburg, St. Petersburg, 1997.
20. M. Daňková, and M. Štěpnička Fuzzy transform as an additive normal form Fuzzy Sets and Systems 157 2006 1024 1035
21. J.G. De Gooijer, and R.J. Hyndman 25 years of time series forecasting International Journal of Forecasting 22 2006 443 473 (Pubitemid 44057710)
22. F. Di Martino, V. Loia, I. Perfilieva, and S. Sessa An image coding/decoding method based on direct and inverse fuzzy transforms International Journal of Approximate Reasoning 48 2008 110 131 (Pubitemid 351324063)
23. F. Di Martino, and S. Sessa Compression and decompression of images with discrete fuzzy transforms Information Sciences 177 2007 2349 2362 (Pubitemid 46435499)
24. F. Di Martino, V. Loia, and S. Sessa Fuzzy transforms method and attribute dependency in data analysis Information Sciences 180 2010 493 505
25. K.M. EL-Naggar, K.A. AL-Rumaih, Genetic based algorithm approach to long-term load forecasting, in: Proceedings of the 6th International Middle East Power Systems Conference, Mansoura, Egypt, vol. 1, 1998, pp. 237-241.
26. K.M. EL-Naggar, K.A. AL-Rumaih, Electric load forecasting using genetic based algorithm, optimal filter estimator and least error squares technique: comparative study, in: Proceedings of the World Academy of Science, Engineering and Technology, vol. 6, 2005, pp. 138-142. (Pubitemid 43194636)
27. N.R. Farnum, and L.W. Stanton Quantitative Forecasting Methods 1989 PWS-KENT Publishing Co. Boston
28. N.E. Goljandina, V.V. Nekrutkin, and A.A. Zhigljavsky Analysis of Time Series Structure: SSA and Related Technique 2001 Chapman & Hall, CRS Boca Raton
29. J.W. Hurrell Decadal trends in the North Atlantic Oscillation: regional temperatures and precipitation Science 269 5224 1995 676 679 (Pubitemid 26439360)
30. J.W. Hurrell, and H. van Loon Decadal variations in climate associated with the North Atlantic Oscillation Climatic Change 36 1997 301 326 (Pubitemid 27353936)
31. H. Inoue, Y. Fukunaga, H. Narisha, Efficient Hybrid Neural Network for Chaotic Time Series Prediction, in: Lecture Notes in Computer Sciences, vol. 2130, 2001, pp. 712-718. (Pubitemid 33317032)
32. H. Ishibuchi, and T. Yamamoto Rule weight specification in fuzzy rule-based classification systems IEEE Transactions on Fuzzy Systems 3 4 2005 428 435 (Pubitemid 41461439)
33. R. Jensen, and Q. Shen Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches 2008 IEEE Press, Wiley & Sons New York
34. A.B. Koehler, R.D. Snyder, and J.K. Ord Forecasting models and prediction intervals for the multiplicative Holt-Winters method International Journal of Forecasting 17 2001 269 286 (Pubitemid 33376294)
35. W. Kolassa, and W. Schutz Advantages of the MAD/MEAN ratio over the MAPE: foresight International Journal of Applied Forecasting 6 2007 40 43
36. A. Lendasse, E. Oja, O. Simula, and M. Verleysen Time series prediction competition: the CATS benchmark Neurocomputing 70 2007 2325 2329 (Pubitemid 46825381)
37. Q. Li, S. Chen, D. Wang, An intelligent runoff forecasting method based on fuzzy sets, neural network and genetic algorithm, in: Proceedings of the International Conference on Intelligent Systems Design and Applications, vol. 1, 2006, pp. 948-953. (Pubitemid 47178961)
38. H. Li, R. Kozma, A dynamic neural network method for time series prediction using the KIII model, in: Proceedings of the International Joint Conference on Neural Networks, vol. 1, 2003, pp. 347-352.
39. B. Li, S. Zhang, and X. Wang Research on fuzzy modeling forecasting method based on stochastic neural network Systems Analysis Modelling Simulation 43 12 2003 1709 1715 (Pubitemid 44112240)
40. G.C. Liao, and T.P. Tsao Application novel GA-based approach and neural fuzzy networks for short-term load forecasting Proceedings of the Power Engineering Society General Meeting vol. 1 2004 IEEE Press 589 594
41. G.C. Liao, and T.P. Tsao Integrated genetic algorithm/tabu search and neural fuzzy networks for short-term load forecasting Proceedings of the Power Engineering Society General Meeting vol. 1 2004 IEEE Press 1082 1087
42. S.G. Makridakis, S.C. Wheelwright, and R.J. Hyndman Forecasting: Methods and Applications third ed. 1998 John Wiley & Son New York
43. E. Mamdani, and S. Assilian An experiment in linguistic synthesis with a fuzzy logic controller International Journal of Man-Machine Studies 7 1975 1 13
44. K. Michels, F. Klawonn, R. Kruse, and A. Nurnberger Fuzzy Control: Fundamentals, Stability and Design of Fuzzy Controllers 2006 Springer Berlin
45. V. Novak, I. Perfilieva, and J. Mockor Mathematical Principles of Fuzzy Logic 1999 Kluwer Boston
46. V. Novak, M. Stepnicka, I. Perfilieva, and V. Pavliska Analysis of periodical time series using soft computing methods Proceedings of FLINS 2008 2008 World Scientific Singapore 55 60
47. K. Nozaki, H. Ishibuchi, and H. Tanaka A simple but powerful heuristic method for generating fuzzy rules from numerical data Fuzzy Sets and Systems 86 1997 251 270 (Pubitemid 127683579)
48. A.K. Palit, D. Popovic, Fuzzy logic automatic rule generation and forecasting of time series, in: Proceedings of the IEEE International Conference on Fuzzy Systems, Seoul, vol. 1, 1999, pp. 360-365.
49. I. Perfilieva Fuzzy transforms: theory and applications Fuzzy Sets and Systems 157 2006 993 1023
50. I. Perfilieva, V. Novk, and A. Dvork Fuzzy transforms in the analysis of data International Journal of Approximate Reasoning 48 2008 36 46
51. I. Perfilieva, V. Novak, V. Pavliska, A. Dvorak, and M. Stepnicka Analysis and prediction of time series using fuzzy transform Proceedings of WCCI 2008 2008 IEEE Computational Intelligence Society Hong Kong 3875 3879
52. L. Sanchez, J. Otero, and I. Couso Obtaining linguistic rule-based regression models from imprecise data with multiobjective genetic algorithms Soft Computing 13 2009 467 469
53. L. Sanchez, J. Otero, J.R. Villar, Boosting of fuzzy models for high dimensional imprecise datasets, in: Proceedings of IPMU, Paris, 2006, pp. 1965-1973.
54. M. Stepnicka, and R. Valasek Fuzzy transforms and their application to wave equation Journal of Electrical Engineering 55 12 2004 7 10
55. M. Stepnicka, V. Pavliska, V. Novak, I. Perfilieva, Time series analysis and prediction based on fuzzy rules and the fuzzy transform, in: Proceedings of IFSA World Congress/EUSFLAT Conference, Lisbona, Universidade Técnica de Lisbona, 2009, pp. 483-488.
56. F. Su, and S.H. Li Neural network based fusion of global and local information in predicting time series Proceedings of the IEEE International Joint Conference on Systems, Man and Cybernetics vol. 5 2003 IEEE Press Washington 4445 4450
57. T. Sudkamp, and R.J. Hammell III Interpolation, completion and learning fuzzy rules IEEE Transactions on Systems, Man, and Cybernetics 24 2 1994 332 342
58. J. Sullivan, and W.H. Woodall A comparison of fuzzy forecasting and Markov modeling Fuzzy Sets and Systems 64 1996 279 293
59. H. Tamura, K. Tanno, H. Tanaka, and Z. Zhang Bi-directional function learning method for times series prediction ICIC Press Letters 2 4 2008 401 407
60. R. Thawonmas, and S. Abe Function approximation based on fuzzy rules extracted from partitioned numerical data IEEE Transactions on Systems, Man, and Cybernetics - Part B 29 4 1999 525 534
61. M. Yar, and C. Chatfield Prediction intervals for the Holt-Winters forecasting procedure International Journal of Forecasting 6 1990 127 137
62. L.X. Wang, and J.M. Mendel Generating fuzzy rules by learning from examples Transactions on Systems, Man, and Cybernetics 22 1992 1414 1427
63. K.W. Wong, D. Tikk, T.D. Gedeon, and L.T. Kóczy Fuzzy rule interpolation for multidimensional input spaces with applications: a case study IEEE Transactions on Fuzzy Systems 13 6 2005 809 819 (Pubitemid 43065964)
64. S. Wu, M.J. Er, and Y. Gao A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks IEEE Transactions on Fuzzy Systems 9 4 2001 578 594 (Pubitemid 32933044)
65. URL 〈 http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao. shtml 〉.