NUI Maynooth

NUIM ePrints and eTheses Archive

NUIM Library

Incorporation of statistical methods in multi-step neural network prediction models

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

[img] Download (663kB)

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;
Subjects: Science & 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
URI:

Repository Staff Only(login required)

View Item Item control page

Document Downloads

More statistics for this item...