Double Quantization of the Regressor Space for Long-Term Time Series Prediction: Method and Proof of Stability
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. © 2004 Elsevier Ltd. All Rights Reserved.
Recommended Citation
G. Simon et al., "Double Quantization of the Regressor Space for Long-Term Time Series Prediction: Method and Proof of Stability," Neural Networks, vol. 17, no. 8 thru 9, pp. 1169 - 1181, Elsevier, Oct 2004.
The definitive version is available at https://doi.org/10.1016/j.neunet.2004.08.008
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Long term forecasting; Method stability proof; SOM; Time series; Trend prediction
International Standard Serial Number (ISSN)
0893-6080
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Elsevier, All rights reserved.
Publication Date
01 Oct 2004
PubMed ID
15555859
