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STORRE: Stirling Online Research Repository
http://hdl.handle.net/1893/3657| Appears in Collections: | Computing Science and Mathematics Journal Articles |
| Peer Review Status: | Refereed |
| Title: | A Novel Neural Network Ensemble Architecture for Time Series Forecasting |
| Author(s): | Gheyas, Iffat A Smith, Leslie |
| Contact Email: | lss@cs.stir.ac.uk |
| Keywords: | Time series forecasting Generalized regression neural networks Neural network ensemble Curse of dimensionality Dynamic nonlinear weighted voting Neural networks (Computer science) Data mining |
| Issue Date: | Nov-2011 |
| Date Deposited: | 24-Feb-2012 |
| Citation: | Gheyas IA & Smith L (2011) A Novel Neural Network Ensemble Architecture for Time Series Forecasting. Neurocomputing, 74 (18), pp. 3855-3864. https://doi.org/10.1016/j.neucom.2011.08.005 |
| Abstract: | We propose a novel homogeneous neural network ensemble approach called Generalized Regression Neural Network (GEFTS-GRNN) Ensemble for Forecasting Time Series, which is a concatenation of existing machine learning algorithms.GEFTS use a dynamic nonlinear weighting system wherein the outputs from several base-level GRNNs are combined using a combiner GRNN to produce the final output. We compare GEFTS with the 11 most used algorithms on 30 real datasets. The proposed algorithm appears to be more powerful than existing ones. Unlike conventional algorithms, GEFTS is effective in forecasting time series with seasonal patterns. |
| DOI Link: | 10.1016/j.neucom.2011.08.005 |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| A Novel Neural Network.pdf | Fulltext - Published Version | 1.11 MB | Adobe PDF | Under Permanent Embargo Request a copy |
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