Double quantization of the regressor space for long-term time series prediction: method and proof of stability.
(2004) Neural Networks — Vol. 17, n° 8-9, p. 1169-1181 (2004)
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- Abstract
- The Kohonen self-organization map is usually considered as a classification or clustering tool, with only a few applications in time series prediction. In this paper, a particular time series forecasting method based on Kohonen maps is described. This method has been specifically designed for the prediction of long-term trends. The proof of the stability of the method for long-term forecasting is given, as well as illustrations of the utilization of the method both in the scalar and vectorial cases.
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Citations
Simon, G., Lendasse, A., Cottrell, M., Fort, J.-C., & Verleysen, M. (2004). Double quantization of the regressor space for long-term time series prediction: method and proof of stability. Neural Networks, 17(8-9), 1169-1181. https://doi.org/10.1016/j.neunet.2004.08.008 (Original work published 2004)