Abstract
In This Paper, Time Series Prediction is Considered as a Problem of Missing Values. a Method for the Determination of the Missing Time Series Values is Presented. the Method is based on Two Projection Methods: A Nonlinear One (Self-Organized Maps) and a Linear One (Empirical Orthogonal Functions). the Presented Global Methodology Combines the Advantages of Both Methods to Get Accurate Candidates for the Prediction Values. the Methods Are Applied to Two Time Series Competition Datasets. ©2007 IEEE.
Recommended Citation
A. Sorjamaa and A. Lendasse, "Time Series Prediction as a Problem of Missing Values: Application to ESTSP2007 and NN3 Competition Benchmarks," IEEE International Conference on Neural Networks - Conference Proceedings, pp. 2948 - 2953, article no. 4371429, Institute of Electrical and Electronics Engineers, Dec 2007.
The definitive version is available at https://doi.org/10.1109/IJCNN.2007.4371429
Department(s)
Engineering Management and Systems Engineering
International Standard Book Number (ISBN)
978-142441380-5
International Standard Serial Number (ISSN)
1098-7576
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Dec 2007
