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Cloarec, Guy-Michel and Ringwood, John (1998) Incorporation of statistical methods in multi-step neural network prediction models. Proceedings of the 1998 IEEE International Joint Conference On Neural Networks, Anchorage, Alaska, 3. pp. 2513-2518. ISSN 1098-7576
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Abstract
This paper addresses the problems associated with multistep ahead prediction neural networks models. We will see how some concepts from the statistical theory field can be applied in various ways to improve the modelling. The generalization and error autocorrelation problems will he addressed using topological and methodological approach among which network committees, statistical bootstrap and principal component analysis will play a key role. These methods will be applied to the sunspot time series
| Item Type: | Article |
|---|---|
| Keywords: | correlation theory; forecasting theory; generalisation (artificial intelligence); neural nets; statistical analysis; error autocorrelation; generalization; |
| Academic Unit: | Faculty of Science and Engineering > Electronic Engineering |
| Item ID: | 1964 |
| Depositing User: | Professor John Ringwood |
| Date Deposited: | 01 Jun 2010 15:12 |
| Journal or Publication Title: | Proceedings of the 1998 IEEE International Joint Conference On Neural Networks, Anchorage, Alaska |
| Publisher: | IEEE |
| Refereed: | Yes |
| Related URLs: | |
| URI: | https://mu.eprints-hosting.org/id/eprint/1964 |
| Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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