Time Series Prediction via Two-Step Clustering
Linear and nonlinear models for time series analysis and prediction are well-established. Clustering methods have also been applied to this area. This paper explores a framework that can be used to cluster time series data. The range of values of a time series is clustered. Then the time series is clustered by data windows that flow into the initial set of value clusters. This allows predictive temporal patterns to be discovered across the whole range of values.
C. Smith and D. C. Wunsch, "Time Series Prediction via Two-Step Clustering," Proceedings of the International Joint Conference on Neural Networks, Institute of Electrical and Electronics Engineers (IEEE), Jan 2015.
The definitive version is available at http://dx.doi.org/10.1109/IJCNN.2015.7280586
International Joint Conference on Neural Networks, IJCNN 2015 (2015: Jul. 12-17, Killarney, Ireland)
Electrical and Computer Engineering
Center for High Performance Computing Research
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.