Patent
1995-02-28
1998-05-05
Hafiz, Tariq R.
395 10, G06F 1518
Patent
active
057488517
ABSTRACT:
An apparatus for executing a short-term prediction of chaotic timeseries data includes a parameter determining section that changes each of parameter values according to the dynamics of observed chaotic timeseries data, and a predicting section that predicts a near future value of objective by reconstructing an attractor of timeseries data of the objective data in a multi-dimensional state space and by using vector neighboring to the data vector including the objective data. Therefore, it becomes possible to quickly and accurately execute a short-term prediction of chaotic timeseries data and to be responsive to the changes of the dynamics of the timeseries data.
REFERENCES:
T. Iokibe et al., "Short-term Prediction on Chaotic Timeseries by Local Fuzzy Reconstruction Method", Proc. Brazil-Japan Joint Symposium on Fuzzy Systems, 1994, pp. 136-139.
T. Iokibe et al., "Short-term Prediction on Chaotic Timeseries by Local Fuzzy Reconstruction Method", Proc. 3rd Intl. Conference on Fuzzy Logic, Neural Nets and Soft Computing, 1994, pp. 491-492.
Weigend et al, "Time Series Prediction: Forecasting the future and understanding the past"; Proceedings of the NATO Advanced Research Workshop on comparative time series analysis held in Santa Fe, NM, pp. 4-29, May, 1992.
Jang, "ANSIF: Adaptive-network-based fuzzy inference system"; IEEE Transactions on systems, Man, and Cybernetics, vol. 23, pp. 665-685, May, 1993.
Weigend et al, "Results of the time series prediction competition at the Santa Fe Institute"; 1993 IEEE International Conference on Neural Networks, pp. 1786-1793, Mar., 1993.
Fujimoto Yasunari
Iokibe Tadashi
Tanimura Takayoshi
Hafiz Tariq R.
Kabushiki Kaisha Meidensha
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