Long-term time series prediction using k-NN based LS-SVM framework with multi-value integration

Recent Trends in Information Reuse and Integration

Volumn , Issue , 2012, Pages 191-209

  Huang, Zifang ^a   Shyu, Mei Ling ^a  

^a University of Miami College of Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY LOGIC; FUZZY NEURAL NETWORKS; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS; SUPPORT VECTOR MACHINES; TIME SERIES;

AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE; EXPONENTIAL SMOOTHING; LONG-TERM TIME SERIES PREDICTIONS; PREDICTION HORIZON; PREDICTION PROBLEM; PREDICTION PROCESS; TIME SERIES MODELING; TIME SERIES PREDICTION;

FORECASTING;

EID: 84868316661     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-7091-0738-6_9     Document Type: Chapter

References (34)

1. Bontempi, G.: Long term time series prediction with multi-input multi-output local learning. In: 2nd European Symposium on Time Series Prediction pp. 145-154 (2008)
2. Clement, M.P., Hendry, D.F.: Forecasting economic times series. Cambridge University Press, Cambridge (1998)
3. Cristi, R., Tummala, M.: Multirate, multiresolution, recursive kalman filter. Signal Process. 80(9), 1945-1958 (2000)
4. Crone, S.F.: Artificial neural network & computational intelligence forecasting competition, www.neural-forecasting-competition.com (2010)
5. Farooq, T., Guergachi, A., Krishnan, S.: Chaotic time series prediction using knowledge based green’s kernel and least-squares support vector machines. In: IEEE International Conference on Systems, Man and Cybernetics pp. 373-378 (2007)
6. Herrera, L.J., Pomares, H., Rojas, I., Guilln, A., Prieto, A., Valenzuela, O.: Recursive prediction for long term time series forecasting using advanced models. Neurocomputing 70(16-18), 2870-2880 (2007)
7. Homma, N., Sakai, M., Takai, Y.: Time series prediction of respiratory motion for lung tumor tracking radiation therapy. In: 10th WSEAS international conference on Neural networks pp. 126-131 (2009)
8. Huang, Z., Shyu, M.L.: k-NN based LS-SVM framework for long-term time series prediction. In: 2010 IEEE International Conference on Information Reuse and Integration pp. 69-74 (2010)
9. Huebner, U., Abraham, N.B., Weiss, C.O.: Dimensions and entropies of chaotic intensity pulsations in a single-mode far-infrared NH3 laser. Phys. Rev. A 40(11), 6354-6365 (1989)
10. Jang, J.S.: Anfis: adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man Cybern. Syst. Hum. 23(3), 665-685 (1993)
11. Jiang, T., Wang, S., Wei, R.: Support vector machine with composite kernels for time series prediction. In: 4th international symposium on Neural Networks pp. 350-356 (2007)
12. Jones, R.H.: Exponential smoothing for multivariate time series. J. Roy. Stat. Soc. B 28(1), 241-251 (1966)
13. Kusiak, A., Zheng, H., Song, Z.: Short-term prediction of wind farm power: A data mining approach. IEEE Trans. Energ. Convers. 24(1), 125-136 (2009)
14. Lin, K., Lin, Q., Zhou, C., Yao, J.: Time series prediction based on linear regression and SVR. Third International Conference on Natural Computation 1, 688-691 (2007)
15. Liu, P., Yao, J.: Application of least square support vector machine based on particle swarm optimization to chaotic time series prediction. In: IEEE International Conference on Intelligent Computing and Intelligent Systems 4, 458-462 (2009)
16. Lotric, U.: Wavelet based denoising integrated into multilayered perceptron. Neurocomputing 62, 179-196 (2004)
17. Mackey, M., Glass, L.: Oscillation and chaos in physiological control systems. Science 197(4300), 287-289 (1977)
18. Maralloo, M., Koushki, A., Lucas, C., Kalhor, A.: Long term electrical load forecasting via a neurofuzzy model. In: 14th International CSI Computer Conference pp. 35-40 (2009)
19. Menezes Jr, J.M.P., Barreto, G.A.: Long-term time series prediction with the narx network: An empirical evaluation. Neurocomputing 71(16-18), 3335-3343 (2008)
20. Meng, K., Dong, Z., Wong, K.: Self-adaptive radial basis function neural network for shortterm electricity price forecasting. IET Gener. Transm. Distrib. 3(4), 325-335 (2009)
21. Nguyen, H.H., Chan, C.W.: Multiple neural networks for a long term time series forecast. Neural. Comput. Appl. 13, 90-98 (2004)
22. Pelckmans, K., Suykens, J.A.K., Gestel, T.V., Brabanter, J.D., Lukas, L., Moor, B.D., Vandewalle, J.: LS-SVMlab toolbox user’s guide. ESAT-SCD-SISTA Technical Report pp. 1-106 (2003)
23. Puma-Villanueva, W.J., dos Santos, E., Von Zuben, F.: Long-term time series prediction using wrappers for variable selection and clustering for data partition. In: International Joint Conference on Neural Networks pp. 3068-3073 (2007)
24. Renaud, O., Starck, J.L., Murtagh, F.: Wavelet-based combined signal filtering and prediction. IEEE Trans. Syst. Man Cybern. B Cybern. 35(6), 1241-1251 (2005)
25. Sapankevych, N., Sankar, R.: Time series prediction using support vector machines: a survey. IEEE Comput. Intell. Mag. 4(2), 24-38 (2009)
26. Sfetsos, A., Siriopoulos, C.: Time series forecasting with a hybrid clustering scheme and pattern recognition. IEEE Trans. Syst. Man Cybern. A Syst. Hum. 34(3), 399-405 (2004)
27. Soltani, S., Boichu, D., Simard, P., Canu, S.: The long-term memory prediction by multiscale decomposition. Signal Process. 80(10), 2195-2205 (2000)
28. Sorjamaa, A., Hao, J., Reyhani, N., Ji, Y., Lendasse, A.: Methodology for long-term prediction of time series. Neurocomputing 70(16-18), 2861-2869 (2007)
29. Suykens, J.A.K., Gestel, T.V., Brabanter, J.D., Moor, B.D., Vandewalle, J.: Least Squares Support Vector Machines. World Scientific, Farrer Road, Singapore (2002)
30. Taieb, S.B., Bontempi, G., Sorjamaa, A., Lendasse, A.: Long-term prediction of time series by combining direct and mimo strategies. In: International Joint Conference on Neural Networks pp. 3054-3061 (2009)
31. Wei, H.L., Billings, S.A.: Long term prediction of non-linear time series using multiresolution wavelet models. Int. J. Contr. 79(6), 569-580 (2006)
32. Yegnanarayana, B.: Artificial Neural Networks. Prentice-Hall of India Pvt. Ltd, New Delhi (2004)
33. Zhang, G.: Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing 50, 159-175 (2003)
34. Zou, H., Yang, Y.: Combining time series models for forecasting. Int. J. Forecast. 20(1), 69-84 (2004)